Methods and apparatus to determine impressions corresponding to market segments

ABSTRACT

An example apparatus includes processor circuitry to access demographics from a database proprietor corresponding to impression requests from computing devices indicative of media impressions, determine a first media impression count corresponding to a sum of first media impressions that occurred on first computing devices satisfying a device type criterion and that are attributable to a demographic group corresponding to a) the demographics from the database proprietor, b) panel-based demographics corresponding to a market segment, determine a second media impression count corresponding to second media impressions that occurred on second computing devices not satisfying the device type criterion and that are attributable to the demographic group corresponding to a) the demographics from the database proprietor, b) the panel-based demographics corresponding to the market segment, and determine a total media impression count by adding the first media impression count to the second media impression count that are attributable to the demographic group.

RELATED APPLICATIONS

This patent arises from a continuation of U.S. patent application Ser.No. 16/429,792, filed on Jun. 3, 2019, which is a continuation of U.S.patent application Ser. No. 14/729,870 (now U.S. Pat. No. 10,311,464),filed on Jun. 3, 2015, which claims priority to U.S. Provisional PatentApplication No. 62/026,001, filed Jul. 17, 2014, and to U.S. ProvisionalPatent Application No. 62/117,253, filed Feb. 17, 2015, all of which arehereby incorporated herein by reference in their entireties.

FIELD OF THE DISCLOSURE

This disclosure relates generally to audience measurement, and, moreparticularly, to methods and apparatus to determine impressionscorresponding to market segments.

BACKGROUND

Techniques for monitoring user access to Internet resources such as webpages, advertisements and/or other media have evolved significantly overthe years. Some prior systems perform such monitoring primarily throughserver logs. In particular, entities serving media on the Internet canuse such prior systems to log the number of requests received for theirmedia at their server. However, such systems lack a means to determineany characteristics about the persons responsible for the loggedrequests.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an example system to collect user information fromdistributed database proprietors for associating with impressions ofmedia presented at a client device in accordance with the teachings ofthis disclosure.

FIG. 2 is a more detailed block diagram of an example implementation ofthe example impression monitoring server of FIG. 1 .

FIG. 3 illustrates example input data and resulting output data toattribute impressions and/or audience sizes to market segments and/ordemographic groups.

FIG. 4 is a flow diagram representative of example computer readableinstructions which may be executed to implement the example impressionmonitoring server of FIGS. 1 and/or 2 to select a panel audience basedon a set of demographic groups at multiple granularity levels to be usedto attribute impressions to a market segment.

FIG. 5 is a flowchart representative of example alternative computerreadable instructions which may be executed to implement the exampleimpression monitoring server of FIGS. 1 and/or 2 to select a panelaudience based on demographic groups and/or day-parts at multiplegranularity levels to be used to attribute impressions to a marketsegment.

FIG. 6 is a flowchart representative of example alternative computerreadable instructions which may be executed to implement the exampleimpression monitoring server of FIGS. 1 and/or 2 to estimate a share fora market segment of interest using a selected demographic granularitylevel.

FIG. 7 is a block diagram of an example processor platform structured toexecute the instructions of FIGS. 4, 5 , and/or 6 to implement theimpression monitoring server of FIGS. 1 and/or 2 .

The figures are not to scale. Wherever appropriate, the same referencenumbers will be used throughout the drawing(s) and accompanying writtendescription to refer to the same or like parts.

DETAILED DESCRIPTION

Techniques for monitoring user access to Internet resources such as webpages, advertisements and/or other media have evolved significantly overthe years. At one point in the past, such monitoring was done primarilythrough server logs. In particular, entities serving media on theInternet would log the number of requests received for their media attheir server. Basing Internet usage research on server logs isproblematic for several reasons. For example, server logs can betampered with either directly or via zombie programs which repeatedlyrequest media from servers to increase the server log countscorresponding to the requested media. Secondly, media is sometimesretrieved once, cached locally and then repeatedly viewed from the localcache without involving the server in the repeat viewings. Server logscannot track these views of cached media because reproducing locallycached media does not require re-requesting the media from a server.Thus, server logs are susceptible to both over-counting andunder-counting errors.

The inventions disclosed in Blumenau, U.S. Pat. No. 6,108,637,fundamentally changed the way Internet monitoring is performed andovercame the limitations of the server side log monitoring techniquesdescribed above. For example, Blumenau disclosed a technique whereinInternet media to be tracked is tagged with beacon instructions. Inparticular, monitoring instructions are associated with the HypertextMarkup Language (HTML) of the media to be tracked. When a clientrequests the media, both the media and the beacon instructions aredownloaded to the client. The beacon instructions are, thus, executedwhenever the media is accessed, be it from a server or from a cache.

The beacon instructions cause monitoring data reflecting informationabout the access to the media to be sent from the client that downloadedthe media to a monitoring entity. Typically, the monitoring entity is anaudience measurement entity (AME) (e.g., any entity interested inmeasuring or tracking audience exposures to advertisements, media,and/or any other media) that did not provide the media to the client andwho is a trusted third party for providing accurate usage statistics(e.g., The Nielsen Company, LLC). Advantageously, because the beaconinginstructions are associated with the media and executed by the clientbrowser whenever the media is accessed, the monitoring information isprovided to the AME irrespective of whether the client is a panelist ofthe AME.

It is useful, however, to link demographics and/or other userinformation to the monitoring information. To address this issue, theAME establishes a panel of users who have agreed to provide theirdemographic information and to have their Internet browsing activitiesmonitored. When an individual joins the panel, they provide detailedinformation concerning their identity and demographics (e.g., gender,race, income, home location, occupation, etc.) to the AME. The AME setsa cookie (or other persistent identifier) on the panelist computer thatenables the AME to identify the panelist whenever the panelist accessestagged media and, thus, sends monitoring information to the AME.

Most of the clients providing monitoring information from the taggedpages are not panelists and, thus, are unknown to the AME. Thus, it isnecessary to use statistical methods to impute demographic informationbased on the data collected for panelists to the larger population ofusers providing data for the tagged media. However, panel sizes of AMEsremain small compared to the general population of users. Thus, aproblem is presented as to how to increase panel sizes while ensuringthe demographics data of the panel are accurate.

There are many database proprietors operating on the Internet. Thesedatabase proprietors provide services (e.g., social networking services,email services, media access services, etc.) to large numbers ofsubscribers. In exchange for the provision of such services, thesubscribers register with the database proprietors. As part of thisregistration, the subscribers provide detailed demographic information.Examples of such database proprietors include social network providerssuch as Facebook, Myspace, Twitter, etc. These database proprietors setcookies on the computers of their subscribers to enable the databaseproprietors to recognize registered users when such registered usersvisit their websites.

Examples disclosed herein can be used to determine media impressions,advertisement impressions, media exposure, and/or advertisement exposurebased on user information, which is distributed across differentdatabases (e.g., different website owners, service providers, etc.) onthe Internet. Not only do example methods, apparatus, and articles ofmanufacture disclosed herein enable more accurate correlation ofInternet media exposure to user information, but they also effectivelyextend panel sizes and compositions beyond persons participating in thepanel of an audience measurement entity and/or a ratings entity topersons registered in other Internet databases such as the databases ofwireless service carriers, mobile software/service providers, socialmedium sites (e.g., Facebook, Twitter, Google, etc.), and/or any otherInternet sites such as Yahoo!, MSN, Apple iTunes, Experian, etc. Thisextension effectively leverages the media impression trackingcapabilities of the AME and the use of databases of non-AME entitiessuch as social media and other websites to create an enormous,demographically accurate panel that results in accurate, reliablemeasurements of exposures to Internet media such as advertising and/orprogramming. Examples of such media include web sites, images presentedon web sites, and/or streaming media accessible via a computing device(e.g., Amazon Video, Netflix, Hulu, etc.).

Traditionally, AMEs (also referred to herein as “ratings entities”)determine demographic reach for advertising and media programming basedon registered panel members. That is, an AME enrolls people who consentto being monitored into a panel. During enrollment, the AME receivesdemographic information from the enrolling people so that subsequentcorrelations may be made between advertisement/media exposure to thosepanelists and different demographic markets. Unlike traditionaltechniques in which AMEs rely solely on their own panel member data tocollect demographics-based audience measurements, example methods,apparatus, and/or articles of manufacture disclosed herein enable an AMEto obtain demographic information shared by other entities (e.g.,database proprietors) that operate based on user registration models tocollect such demographic information. In some examples, the AME alsoshares its panel member demographic information with such other entities(e.g., database proprietors). Such entities may be referred to as“database proprietors” and include entities such as wireless servicecarriers, mobile software/service providers, social medium sites (e.g.,Facebook, Twitter, Google, etc.), and/or any other Internet sites suchas Yahoo!, MSN, Apple iTunes, Experian, etc. that collect demographicdata of users which may be in exchange for a service.

As used herein, a user registration model is a model in which userssubscribe to services of database proprietors by creating an account andproviding demographic-related information about themselves. Receivingdemographic information associated with registered users of databaseproprietors at an AME enables the AME to extend or supplement theirpanel data with substantially reliable demographics information fromexternal sources (e.g., database proprietors), thus extending thecoverage, accuracy, and/or completeness of their demographics-basedaudience measurements. Such access also enables the AME to measurepersons who would not otherwise have joined an AME panel. Any entityhaving a database identifying demographics of a set of individuals maycooperate with the AME.

Examples disclosed herein may be implemented by an AME (e.g., any entityinterested in measuring or tracking audience exposures toadvertisements, content, and/or any other media) in cooperation with anynumber of database proprietors, such as online web services providers,to develop online media exposure metrics. Such databaseproprietors/online web services providers may be wireless servicecarriers, mobile software/service providers, social network sites (e.g.,Facebook, Twitter, MySpace, etc.), multi-service sites (e.g., Yahoo!,Google, Axiom, Catalina, etc.), online retailer sites (e.g., Amazon.com,Buy.com, etc.), credit reporting sites (e.g., Experian) and/or any otherweb service(s) site that maintains user registration records.

The use of demographic information from disparate data sources, such asdatabase proprietors, (e.g., high-quality demographic information fromthe panels of an audience measurement entity and/or registered user dataof web service providers) results in improved reporting effectiveness ofmetrics for both online and offline advertising campaigns. Exampletechniques disclosed herein use online registration data to identifydemographics of users, and/or other user information, and use serverimpression counts, and/or other techniques to track quantities ofimpressions attributable to those users. Online web service providerssuch as wireless service carriers, mobile software/service providers,social network sites (e.g., Facebook, Twitter, MySpace, etc.),multi-service sites (e.g., Yahoo!, Google, Axiom, Catalina, etc.),online retailer sites (e.g., Amazon.com, Buy.com, etc.), creditreporting services (e.g., Experian), etc. (collectively and individuallyreferred to herein as online database proprietors) maintain detaileddemographic information (e.g., age, gender, geographic location, race,income level, education level, religion, etc.) collected via userregistration processes.

An impression corresponds to a home or individual having been exposed tothe corresponding media and/or advertisement. Thus, an impressionrepresents a home or an individual having been exposed to anadvertisement or media or group of advertisements or media. In Internetadvertising, a quantity of impressions, also referred to as impressioncounts, is the total number of times an advertisement or advertisementcampaign has been accessed by a web population (e.g., including thenumber of times accessed as decreased by, for example, pop-up blockersand/or increased by, for example, retrieval from local cache memory). Anamount of time for which there was exposure may also be measured. Asused herein, the term “duration unit” is defined to be an impressionthat corresponds to a period of time, such as 10 seconds, 30 seconds, aminute, or any other unit. For example, if two minutes of a video areviewed and a duration unit corresponds to one minute, two duration unitsare credited to the video due to the viewing.

Impression data is collected from mobile devices that extend beyondmobile device panels (e.g., impression data is collected from every userof a particular application on the mobile device, whether or not theuser of the mobile device is a member of a panel of mobile deviceusers). While the database proprietors that provide demographicinformation corresponding to the impressions enable the impressions tobe attributed to certain defined demographic groups (e.g., age/gendergroups), the database proprietors may not be able to provide informationabout other demographic factor and/or market segments of interest (e.g.,household income, ethnicity, etc.). In such circumstances, impressioninformation cannot be determined or reported for these demographicfactors and/or market segments using the database proprietorinformation.

Furthermore, mobile device audience measurement panels may not havedemographic or market segment characteristics that are comparable to theactual audience of an item of media that corresponds to the impressions.As a result, market segment information derived from such mobile deviceaudience measurement panels may be biased, even significantly biased,thereby introducing bias error into the resulting market segment shareestimate. Panels of mobile device users may be incomplete because, amongother reasons, panelist metering software (used to monitor panelistactivity on the mobile devices) may not be installed and/or may not beinstallable on some types of mobile devices. The absence of meteringsoftware may occur because, for example, such metering software is notgranted sufficient permissions to provide useful data and/or suchmetering software requires excess computing resources (e.g., computingresources that negatively affect the exposure of the user using thecomputing device (e.g., prospective panelists) to a degree in excess ofa level that is considered tolerable). For this reason, current mobiledevice panels may likewise suffer from significant bias error whenapplied to media impressions for the purposes of analyzing marketsegment share.

Examples disclosed herein use a hierarchical approach to estimate apanel audience for the panel-based market segment share. As explained inmore detail below, the panel-based market segment share estimate may bedependent on a panel sample size being at least a threshold size (e.g.,the panel including at least a threshold number of people). A panel is aset of audience members recruited by an audience measurement entity foraudience measurement purposes. Panelists provide detailed demographicinformation to the audience measurement entity and agree to permit theaudience measurement entity to monitor their media exposure habits. Thepanel is created and maintained by the audience measurement entity formeasuring audience behavior as a representative sample of an audience ofinterest (e.g., a portion of the panel audience meeting certaindemographic criteria). In some examples, the audience measurement panel(e.g., a television audience panel, a cross-platform audience panel, aradio audience panel, etc.) used to determine the panel-based marketsegment share mentioned above is selected based on a number of personsof an audience panel in a demographic group and availability of datarepresentative of the media corresponding to the media impressions.

In some disclosed examples, media impression information is collected byan audience measurement entity in cooperation with one or more databaseproprietors. The example audience measurement entity (or another party)attributes (or allocates) collected impressions to the appropriatedemographic groups. This attribution process includes correcting fordata collection errors and/or biases. Example methods and apparatus tocollect impression data and to attribute demographic information to theimpression data are disclosed in U.S. patent application Ser. No.14/560,947, filed Dec. 4, 2014. The entirety of U.S. patent applicationSer. No. 14/560,947 is incorporated herein by reference.

In addition to the demographic makeup of a set of impressions that canbe provided by the database proprietor, advertisers may also beinterested in one or more specific market segments not available from(and/or not fully represented by the data of) the database proprietor.Such market segments may represent specific portions of the audiencethat have one or more common characteristics (e.g., race, gender, nativelanguage, income, political affiliation, etc.) and who, as a group, aremore likely (or less likely) to respond to a stimulus with a particularbehavior than the audience as a whole.

As used herein, the term “market segment” refers to a group of peoplewho have or are estimated to have one or more common characteristics. Asused herein, the terms “demographics,” “demographic data,” “demographiccharacteristics,” and/or “demographic information” refer tocharacteristics that describe a particular person or group of people.Example demographic information includes age, gender, race, income,native language, home location, and/or occupation. In some examples, amarket segment of interest is specified using, among other things, oneor more demographic characteristics. As used herein, a share of mediaimpressions for a market segment of interest (also referred to as amarket segment share) refers to a subset or portion of a largercollection of impressions corresponding to a particular market segmentof interest and logged in connection with numerous other marketsegments.

As an example, in the television ratings context, market segments may bedetermined by consulting a television audience measurement panel, suchas the Nielsen National TV Ratings Panel, that is statistically selectedto be representative of the total audience including many marketsegments. To determine the market share for a market segment in thetelevision ratings context, an audience measurement entity, such as TheNielsen Company, may determine the portion of the total televisionaudience who are in the market segment of interest. The audiencemeasurement entity then determines the market share for the marketsegment of interest (e.g., a percentage of the audience that isrepresented by the market segment) by dividing the determined portion bythe total estimated audience size.

Examples disclosed herein determine a share (or portion) of mediaimpressions occurring on mobile devices that are attributable to amarket segment of interest. In examples disclosed herein, a share refersto a portion of impressions that is a subset of a larger group ofimpressions. In some examples, the market segment of interest is notidentifiable by a database proprietor from which demographic informationcorresponding to the media impressions is obtained because, for example,the database proprietor does not or cannot collect market segmentinformation for the market segment of interest. The market segment ofinterest may be defined by a demographic characteristic that is unknownto the database proprietor. In some disclosed examples, an audiencepanel for a different media platform (e.g., a television audience panel,a radio audience panel, a PC audience panel, etc.) is used to determinethe share of media impressions for the market segment of interest, wherethe audience panel has information about the market segment of interest(e.g., the audience panel has access to the characteristic defining themarket segment, which characteristic is not known by the databaseproprietor). In some examples, the panel is selected to have an audiencewhose media access behaviors are as similar as possible to the mediaaccess behaviors of the mobile device audience corresponding to themedia impressions.

Examples disclosed herein use a hierarchical process to calculate amarket segment share at a most detailed (e.g., granular) level possiblefor which accurate data is available. This determination of the level ofdetail possible is made by identifying one or more relevant data setsthat achieve a specified precision for the estimated market segmentshare. For example, the AME may divide panelists into demographic groupsat multiple levels (e.g., hierarchical levels) that range from moregranular to less granular by demographic composition. Examplehierarchical levels are shown in Table 1 below, in order from leastgranular level (e.g., Male) to most granular level (e.g., Male, Age24-35, Income >100K).

TABLE 1 Example Hierarchical Levels Granularity Levels Number ofPanelists Male 100,000 Male, Age 24-35 20,000 Male, Age 24-35, Income >100K 3,000

As used herein, the term “precision” refers to the amount of samplingerror associated with a given metric. Typically, precision increases assample size increases, and decreases as sample size decreases. As usedherein, the term “sample size” refers to the number of panelistsexhibiting the behavior of interest (for example, in the audience).However, references to sample size may be replaced with direct measuresof precision such as standard error or variance, in which caserequirements of sample size thresholds (e.g., minimum sample sizethresholds) would be replaced with standard error or variance thresholds(e.g., a maximum standard error threshold, a maximum variancethreshold).

If the sample size associated with the market segment share is smallerthan a threshold for a particular demographic group (e.g., females,21-24 years old), disclosed examples combine multiple demographic groups(e.g., the group females, 21-24, the group females, 18-21, and the groupfemales, 24-30) to calculate the market segment share for a larger,combined demographic group (e.g., females, 18-30), which is then used tocalculate the impressions attributable to the market segment for one ormore of the more detailed demographic groups in the combined groups.Disclosed examples may combine demographic groups multiple times (e.g.,combine females 21-24 and females 18-20 to females 18-24, combinefemales 18-24 and females 25-30 to females 18-30, etc.). Combination maybe performed at any level(s) in a hierarchy of demographic groups and/ormay be performed on portions of any level(s) in the hierarchy ofdemographic groups, as described in more detail below. Combiningmultiple demographic groups increases the sample size and improves theprecision for the resulting estimated market segment share. However,each collapse of two or more demographic groups sacrifices granularityand/or potentially increases bias error of the demographic informationattributable to the media impressions. By selecting the appropriategranularity and/or sample size, disclosed examples enable determiningmarket segment share for media impressions that occur on mobile deviceswith an precision that was unattainable using previous methods.

Examples disclosed herein may be used with the Online Campaign Ratings(OCR) systems developed by The Nielsen Company (US), LLC.

Disclosed example methods involve receiving, at a first Internet domain,a first request from a computing device. In the disclosed examplemethods, the first request is indicative of access to media at thecomputing device. The disclosed example methods further involverequesting demographic information from a database proprietor, where thedemographic information corresponds to the first request. The disclosedexample methods further involve determining a number of mediaimpressions that occurred on mobile devices and that are attributable toa first demographic group, where the number of media impressions isbased on attributions of the media impressions to the first demographicgroup by the database proprietor in the demographic information. Thedisclosed example methods further involve determining whether a firstsize of a first audience that corresponds to the first demographic groupsatisfies a threshold, the first audience including panelists in anaudience measurement panel maintained by an audience measurement entity.The disclosed example methods further involve determining whether asecond size of a second audience satisfies the threshold when the firstsize of the first audience does not satisfy the threshold. In thedisclosed example methods, the second audience includes panelists in theaudience measurement panel corresponding to a second demographic group,the first audience is a subset of the second audience, and the firstdemographic group is a subset of the second demographic group. Thedisclosed example methods further involve calculating a portion of themedia impressions attributable to a market segment and to the seconddemographic group, based on a portion of the second audience thatbelongs to the market segment, when the second size of the secondaudience satisfies the threshold.

In some disclosed example methods, the threshold includes a minimumnumber of panel audience members. In some disclosed examples, the firstdemographic group includes one of multiple age and gender groups, andthe second demographic group includes a combination of the multiple ageand gender groups. In some such example methods, the audiencemeasurement panel comprises a television audience measurement panel.

Some disclosed example methods further involve determining whether asize of a third audience that corresponds to a third demographic groupsatisfies the threshold, the third audience comprising panelists in theaudience measurement panel, where the third audience is a subset of thesecond audience and the third demographic group is a subset of thesecond demographic group. When the size of the third audience satisfiesthe threshold and the size of the first audience does not satisfy thethreshold, such example methods further involve calculating a secondportion of the media impressions attributable to both the market segmentand the third demographic group based on a portion of the third audiencethat belongs to the market segment, and calculating a portion of themedia impressions attributable to both the market segment and the firstdemographic group based on the portion of the second audience thatbelongs to the market segment.

In some disclosed example methods calculating the portion of the mediaimpressions involves multiplying a) the portion of the second audiencebelonging to the market segment and b) an audience size for the seconddemographic group, where the second demographic group is determinedbased on i) demographic information obtained from the databaseproprietor and ii) a number of media impressions counted at animpression collector, to calculate a portion of the second audience thatbelongs to both the market segment and the second demographic group. Insome such example methods, calculating the portion of the mediaimpressions involves multiplying an impression frequency determined fromthe database proprietor and the portion of the second audience thatbelongs to both the market segment and the second demographic group.

Some disclosed example methods further involve conserving at least oneof computing resources or network resources by calculating the portionof the media impressions attributable to the market segment and to thesecond demographic group without communicating with non-panel onlineusers to request survey responses about their personal details relatedto the market segment.

Disclosed example apparatus include an impression collector, ademographics determiner, a precision determiner, and a market segmentcalculator. In disclosed example apparatus, the impression collectorreceives, at a first Internet domain, a first request from a computingdevice, where the first request is indicative of access to media at thecomputing device. In the disclosed example apparatus, the impressioncollector also requests demographic information from a databaseproprietor, where the demographic information corresponding to the firstrequest. In the disclosed example apparatus, the demographics determinerdetermines a number of media impressions that occurred on mobile devicesand that are attributable to a first demographic group. In the disclosedexample apparatus, the number of media impressions is based onattributions of the media impressions to the first demographic group bythe database proprietor in the demographic information. In the disclosedexample apparatus, the precision determiner determines whether a firstsize of a first audience that corresponds to the first demographic groupsatisfies a threshold, where the first audience includes panelists in anaudience measurement panel maintained by an audience measurement entity.In the disclosed example apparatus, the precision determiner alsodetermines whether a second size of a second audience satisfies thethreshold when the first size of the first audience does not satisfy thethreshold, where the second audience includes panelists in the audiencemeasurement panel and corresponds to a second demographic group. In thedisclosed example apparatus, the first audience is a subset of thesecond audience and the first demographic group is a subset of thesecond demographic group. In the disclosed example apparatus, the marketsegment calculator calculates a portion of the media impressionsattributable to a market segment and to the second demographic group,based on a portion of the second audience that belongs to the marketsegment, when the second size of the second audience satisfies thethreshold.

In some disclosed examples, the threshold is a minimum audience size. Insome example apparatus, the first demographic group includes one ofmultiple age and gender groups, and the second demographic groupincludes a combination of the multiple age and gender groups. In someexamples, the audience measurement panel comprises a television audiencemeasurement panel.

In some disclosed example apparatus, the precision determiner determineswhether a third size of a third audience that corresponds to a thirddemographic group satisfies the threshold, where the third audienceincludes panelists in the audience measurement panel. In such disclosedexample apparatus, the third audience is a subset of the secondaudience, and the third demographic group is a subset of the seconddemographic group. In such example apparatus, when the third size of thethird audience satisfies the threshold and the first size of the firstaudience does not satisfy the threshold: the market segment calculatorcalculates a second portion of the media impressions attributable toboth the market segment and the second demographic group based on aportion of the third audience that belongs to the market segment andcalculates a portion of the media impressions attributable to both themarket segment and the first demographic group based on the portion ofthe second audience that belongs to the market segment.

In some disclosed example apparatus, the market segment calculatorcalculates the portion of the media impressions by multiplying a) theportion of the second audience belonging to the market segment and b) anaudience size for the second demographic group determined based on i)demographic information obtained from the database proprietor and ii) anumber of media impressions counted at the impression collector, tocalculate a portion of the second audience that belongs to both themarket segment and the second demographic group. In some such exampleapparatus, the market segment calculator calculates the portion of themedia impressions by multiplying an impression frequency determined fromthe database proprietor and the portion of the second audience thatbelongs to both the market segment and the second demographic group.

In some disclosed example apparatus, the market segment calculatorconserves at least one of computing resources or network resources bycalculating the portion of the media impressions attributable to themarket segment and to the second demographic group without communicatingwith non-panel online users to request survey responses about theirpersonal details related to the market segment.

While examples disclosed herein are described with reference tocompensating or adjusting impression information obtained from mobiledevices, the examples are also applicable to non-mobile devices such asdesktop computers, televisions, video game consoles, set top boxes,and/or other devices.

Examples disclosed herein can be applied to incoming data in real-timeor substantially real-time (e.g., within seconds or minutes of receivingthe data), and may be used to attribute impression information to marketsegments (e.g., impressions, duration units) for any desirable timeperiod (e.g., hourly, daily, weekly, monthly, etc.) and/or cumulatively(e.g., applied to impressions and/or duration units collected overnumerous time periods). Therefore, examples disclosed herein may provideaccurate market segment information to advertisers and/or mediadistributors to enable more rapid adjustment of media campaignstrategies to fit measured market segments than known methods.

Impression and Demographic Information Collection

FIG. 1 depicts an example system 100 to collect user information (e.g.,user information 102 a, 102 b) from distributed database proprietors 104a, 104 b for associating with impressions of media presented at a clientdevice 106. In the illustrated examples, user information 102 a, 102 bor user data includes one or more of demographic data, purchase data,and/or other data indicative of user activities, behaviors, and/orpreferences related to information accessed via the Internet, purchases,media accessed on electronic devices, physical locations (e.g., retailor commercial establishments, restaurants, venues, etc.) visited byusers, etc. Examples disclosed herein are described in connection withthe client device 106 being a mobile device, which may be a mobilephone, a mobile communication device, a tablet, a gaming device, aportable media presentation device, etc. However, examples disclosedherein may be implemented in connection with non-mobile devices such asInternet appliances, smart televisions, Internet terminals, computers,or any other device capable of presenting media received via networkcommunications.

In the illustrated example of FIG. 1 , to track media impressions on theclient device 106, an audience measurement entity (AME) 108 partnerswith or cooperates with an app publisher 110 to download and install adata collector 112 on the client device 106. The app publisher 110 ofthe illustrated example may be a software app developer that developsand distributes apps to mobile devices and/or a distributor thatreceives apps from software app developers and distributes the apps tomobile devices. The data collector 112 may be included in other softwareloaded onto the client device 106, such as the operating system (OS)114, an application (or app) 116, a web browser 117, and/or any othersoftware. The example client device 106 of FIG. 1 is a non-locallymetered device. That is, the client device 106 does not support and/orhas not been provided with dedicated metering software (e.g., meteringsoftware provided by the AME 108).

Any of the example software 114-117 may present media 118 received froma media publisher 120. The media 118 may be an advertisement, video,audio, text, a graphic, a web page, news, educational media,entertainment media, and/or any other type of media. In the illustratedexample, a media ID 122 is provided in the media 118 to enableidentifying the media 118 so that the AME 108 can credit the media 118with media impressions when the media 118 is presented on the clientdevice 106 or any other device that is monitored by the AME 108.

The data collector 112 of the illustrated example includes instructions(e.g., Java, java script, or any other computer language or script)that, when executed by the client device 106, cause the client device106 to collect the media ID 122 of the media 118 presented by the appprogram 116 and/or the client device 106, and to collect one or moredevice/user identifier(s) 124 stored in the client device 106. Thedevice/user identifier(s) 124 of the illustrated example includeidentifiers that can be used by corresponding ones of the partnerdatabase proprietors 104 a-b to identify the user or users of the clientdevice 106, and to locate user information 102 a-b corresponding to theuser(s). For example, the device/user identifier(s) 124 may includehardware identifiers (e.g., an international mobile equipment identity(IMEI), a mobile equipment identifier (MEID), a media access control(MAC) address, etc.), an app store identifier (e.g., a Google AndroidID, an Apple ID, an Amazon ID, etc.), an open source unique deviceidentifier (OpenUDID), an open device identification number (ODIN), alogin identifier (e.g., a username), an email address, user agent data(e.g., application type, operating system, software vendor, softwarerevision, etc.), third-party service identifiers (e.g., advertisingservice identifiers, device usage analytics service identifiers,demographics collection service identifiers), web storage data, documentobject model (DOM) storage data, local shared objects (also referred toas “Flash cookies”), etc. In some examples, fewer or more device/useridentifier(s) 124 may be used. In addition, although only two partnerdatabase proprietors 104 a-b are shown in FIG. 1 , the AME 108 maypartner with any number of partner database proprietors to collectdistributed user information (e.g., the user information 102 a-b).

In some examples, the client device 106 may not allow access toidentification information stored in the client device 106. For suchinstances, the disclosed examples enable the AME 108 to store anAME-provided identifier (e.g., an identifier managed and tracked by theAME 108) in the client device 106 to track media impressions on theclient device 106. For example, the AME 108 may provide instructions inthe data collector 112 to set an AME-provided identifier in memory spaceaccessible by and/or allocated to the app program 116, and the datacollector 112 uses the identifier as a device/user identifier 124. Insuch examples, the AME-provided identifier set by the data collector 112persists in the memory space even when the app program 116 and the datacollector 112 are not running. In this manner, the same AME-providedidentifier can remain associated with the client device 106 for extendeddurations. In some examples in which the data collector 112 sets anidentifier in the client device 106, the AME 108 may recruit a user ofthe client device 106 as a panelist, and may store user informationcollected from the user during a panelist registration process and/orcollected by monitoring user activities/behavior via the client device106 and/or any other device used by the user and monitored by the AME108. In this manner, the AME 108 can associate user information of theuser (from panelist data stored by the AME 108) with media impressionsattributed to the user on the client device 106.

In the illustrated example, the data collector 112 sends the media ID122 and the one or more device/user identifier(s) 124 as collected data126 to the app publisher 110. Alternatively, the data collector 112 maybe configured to send the collected data 126 to another collectionentity (other than the app publisher 110) that has been contracted bythe AME 108 or is partnered with the AME 108 to collect media ID's(e.g., the media ID 122) and device/user identifiers (e.g., thedevice/user identifier(s) 124) from mobile devices (e.g., the clientdevice 106). In the illustrated example, the app publisher 110 (or acollection entity) sends the media ID 122 and the device/useridentifier(s) 124 as impression data 130 to an impression monitoringserver 132 at the AME 108. The impression data 130 of the illustratedexample may include one media ID 122 and one or more device/useridentifier(s) 124 to report a single impression of the media 118, or itmay include numerous media ID's 122 and device/user identifier(s) 124based on numerous instances of collected data (e.g., the collected data126) received from the client device 106 and/or other mobile devices toreport multiple impressions of media.

In the illustrated example, the impression monitoring server 132 storesthe impression data 130 in an AME media impressions store 134 (e.g., adatabase or other data structure). Subsequently, the AME 108 sends thedevice/user identifier(s) 124 to corresponding partner databaseproprietors (e.g., the partner database proprietors 104 a-b) to receiveuser information (e.g., the user information 102 a-b) corresponding tothe device/user identifier(s) 124 from the partner database proprietors104 a-b so that the AME 108 can associate the user information withcorresponding media impressions of media (e.g., the media 118) presentedat mobile devices (e.g., the client device 106).

In some examples, to protect the privacy of the user of the clientdevice 106, the media identifier 122 and/or the device/useridentifier(s) 124 are encrypted before they are sent to the AME 108and/or to the partner database proprietors 104 a-b. In other examples,the media identifier 122 and/or the device/user identifier(s) 124 arenot encrypted.

After the AME 108 receives the device/user identifier(s) 124, the AME108 sends device/user identifier logs 136 a-b to corresponding partnerdatabase proprietors (e.g., the partner database proprietors 104 a-b).In some examples, each of the device/user identifier logs 136 a-b mayinclude a single device/user identifier, or it may include numerousaggregate device/user identifiers received over time from one or moremobile devices. After receiving the device/user identifier logs 136 a-b,each of the partner database proprietors 104 a-b looks up its userscorresponding to the device/user identifiers 124 in the respective logs136 a-b. In this manner, each of the partner database proprietors 104a-b collects user information 102 a-b corresponding to users identifiedin the device/user identifier logs 136 a-b for sending to the AME 108.For example, if the partner database proprietor 104 a is a wirelessservice provider and the device/user identifier log 136 a includes IMEInumbers recognizable by the wireless service provider, the wirelessservice provider accesses its subscriber records to find users havingIMEI numbers matching the IMEI numbers received in the device/useridentifier log 136 a. When the users are identified, the wirelessservice provider copies the users' user information to the userinformation 102 a for delivery to the AME 108.

In some other examples, the data collector 112 is configured to collectthe device/user identifier(s) 124 from the client device 106. Theexample data collector 112 sends the device/user identifier(s) 124 tothe app publisher 110 in the collected data 126, and it also sends thedevice/user identifier(s) 124 to the media publisher 120. In such otherexamples, the data collector 112 does not collect the media ID 122 fromthe media 118 at the client device 106 as the data collector 112 does inthe example system 100 of FIG. 1 . Instead, the media publisher 120 thatpublishes the media 118 to the client device 106 retrieves the media ID122 from the media 118 that it publishes. The media publisher 120 thenassociates the media ID 122 to the device/user identifier(s) 124received from the data collector 112 executing in the client device 106,and sends collected data 138 to the app publisher 110 that includes themedia ID 122 and the associated device/user identifier(s) 124 of theclient device 106. For example, when the media publisher 120 sends themedia 118 to the client device 106, it does so by identifying the clientdevice 106 as a destination device for the media 118 using one or moreof the device/user identifier(s) 124 received from the client device106. In this manner, the media publisher 120 can associate the media ID122 of the media 118 with the device/user identifier(s) 124 of theclient device 106 indicating that the media 118 was sent to theparticular client device 106 for presentation (e.g., to generate animpression of the media 118).

In some other examples in which the data collector 112 is configured tosend the device/user identifier(s) 124 to the media publisher 120, thedata collector 112 does not collect the media ID 122 from the media 118at the client device 106. Instead, the media publisher 120 thatpublishes the media 118 to the client device 106 also retrieves themedia ID 122 from the media 118 that it publishes. The media publisher120 then associates the media ID 122 with the device/user identifier(s)124 of the client device 106. The media publisher 120 then sends themedia impression data 130, including the media ID 122 and thedevice/user identifier(s) 124, to the AME 108. For example, when themedia publisher 120 sends the media 118 to the client device 106, itdoes so by identifying the client device 106 as a destination device forthe media 118 using one or more of the device/user identifier(s) 124. Inthis manner, the media publisher 120 can associate the media ID 122 ofthe media 118 with the device/user identifier(s) 124 of the clientdevice 106 indicating that the media 118 was sent to the particularclient device 106 for presentation (e.g., to generate an impression ofthe media 118). In the illustrated example, after the AME 108 receivesthe impression data 130 from the media publisher 120, the AME 108 canthen send the device/user identifier logs 136 a-b to the partnerdatabase proprietors 104 a-b to request the user information 102 a-b asdescribed above in connection with FIG. 1 .

Although the media publisher 120 is shown separate from the apppublisher 110 in FIG. 1 , the app publisher 110 may implement at leastsome of the operations of the media publisher 120 to send the media 118to the client device 106 for presentation. For example, advertisementproviders, media providers, or other information providers may sendmedia (e.g., the media 118) to the app publisher 110 for publishing tothe client device 106 via, for example, the app program 116 when it isexecuting on the client device 106. In such examples, the app publisher110 implements the operations described above as being performed by themedia publisher 120.

Additionally or alternatively, in contrast with the examples describedabove in which the client device 106 sends identifiers to the audiencemeasurement entity 108 (e.g., via the application publisher 110, themedia publisher 120, and/or another entity), in other examples theclient device 106 (e.g., the data collector 112 installed on the clientdevice 106) sends the identifiers (e.g., the user/device identifier(s)124) directly to the respective database proprietors 104 a, 104 b (e.g.,not via the AME 108). In such examples, the example client device 106sends the media identifier 122 to the audience measurement entity 108(e.g., directly or through an intermediary such as via the applicationpublisher 110), but does not send the media identifier 122 to thedatabase proprietors 104 a-b.

As mentioned above, the example partner database proprietors 104 a-bprovide the user information 102 a-b to the example AME 108 for matchingwith the media identifier 122 to form media impression information. Asalso mentioned above, the database proprietors 104 a-b are not providedcopies of the media identifier 122. Instead, the client provides thedatabase proprietors 104 a-b with impression identifiers 140. Animpression identifier uniquely identifies an impression event relativeto other impression events of the client device 106 so that anoccurrence of an impression at the client device 106 can bedistinguished from other occurrences of impressions. However, theimpression identifier 140 does not itself identify the media associatedwith that impression event. In such examples, the impression data 130from the client device 106 to the AME 108 also includes the impressionidentifier 140 and the corresponding media identifier 122. To match theuser information 102 a-b with the media identifier 122, the examplepartner database proprietors 104 a-b provide the user information 102a-b to the AME 108 in association with the impression identifier 140 forthe impression event that triggered the collection of the userinformation 102 a-b. In this manner, the AME 108 can match theimpression identifier 140 received from the client device 106 to acorresponding impression identifier 140 received from the partnerdatabase proprietors 104 a-b to associate the media identifier 122received from the client device 106 with demographic information in theuser information 102 a-b received from the database proprietors 104 a-b.The impression identifier 140 can additionally be used for reducing oravoiding duplication of demographic information. For example, theexample partner database proprietors 104 a-b may provide the userinformation 102 a-b and the impression identifier 140 to the AME 108 ona per-impression basis (e.g., each time a client device 106 sends arequest including an encrypted identifier 124-b and an impressionidentifier 140 to the partner database proprietor 104 a-b) and/or on anaggregated basis (e.g., send a set of user information 102 a-b, whichmay include indications of multiple impressions at a mobile device 102a-b (e.g., multiple impression identifiers 140), to the AME 108presented at the client device 106).

The impression identifier 140 provided to the AME 108 enables the AME108 to distinguish unique impressions and avoid overcounting a number ofunique users and/or devices viewing the media. For example, therelationship between the user information 102 a from the partner Adatabase proprietor 104 a and the user information 102 b from thepartner B database proprietor 104 b for the client device 106 is notreadily apparent to the AME 108. By including an impression identifier140 (or any similar identifier), the example AME 108 can associate userinformation corresponding to the same user between the user information102 a-b based on matching impression identifiers 140 stored in both ofthe user information 102 a-b. The example AME 108 can use such matchingimpression identifiers 140 across the user information 102 a-b to avoidovercounting mobile devices and/or users (e.g., by only counting uniqueusers instead of counting the same user multiple times).

A same user may be counted multiple times if, for example, an impressioncauses the client device 106 to send multiple user/device identifiers tomultiple different database proprietors 104 a-b without an impressionidentifier (e.g., the impression identifier 140). For example, a firstone of the database proprietors 104 a sends first user information 102 ato the AME 108, which signals that an impression occurred. In addition,a second one of the database proprietors 104 b sends second userinformation 102 b to the AME 108, which signals (separately) that animpression occurred. In addition, separately, the client device 106sends an indication of an impression to the AME 108. Without knowingthat the user information 102 a-b is from the same impression, the AME108 has an indication from the client device 106 of a single impressionand indications from the database proprietors 104 a-b of multipleimpressions.

To avoid overcounting impressions, the AME 108 can use the impressionidentifier 140. For example, after looking up user information 102 a-b,the example partner database proprietors 104 a-b transmit the impressionidentifier 140 to the AME 108 with corresponding user information 102a-b. The AME 108 matches the impression identifier 140 obtained directlyfrom the client device 106 to the impression identifier 140 receivedfrom the database proprietors 104 a-b with the user information 102 a-bto thereby associate the user information 102 a-b with the mediaidentifier 122 and to generate impression information. This is possiblebecause the AME 108 received the media identifier 122 in associationwith the impression identifier 140 directly from the client device 106.Therefore, the AME 108 can map user data from two or more databaseproprietors 104 a-b to the same media exposure event, thus avoidingdouble counting.

Each unique impression identifier 140 in the illustrated example isassociated with a specific impression of media on the client device 106.The partner database proprietors 104 a-b receive the respectiveuser/device identifiers 124 and generate the user information 102 a-bindependently (e.g., without regard to others of the partner databaseproprietors 104 a-b) and without knowledge of the media identifier 122involved in the impression. Without an indication that a particular userdemographic profile in the user information 102 a (received from thepartner database proprietor 104 a) is associated with (e.g., the resultof) the same impression at the client device 106 as a particular userdemographic profile in the user information 102 b (received from thepartner database proprietor 104 b independently of the user information102 a received from the partner database proprietor 104 a), and withoutreference to the impression identifier 140, the AME 108 may not be ableto associate the user information 102 a with the user information 102 band/or cannot determine that the different pieces of user information102 a-b are associated with a same impression and could, therefore,count the user information 102 a and the user information 102 b ascorresponding to two different users/devices and/or two differentimpressions.

The above examples illustrate methods and apparatus for collectingimpression data at an audience measurement entity (or other entity). Theexamples discussed above may be used to collect impression informationfor any type of media, including static media (e.g., advertisingimages), streaming media (e.g., streaming video and/or audio, includingcontent, advertising, and/or other types of media), and/or other typesof media. For static media (e.g., media that does not have a timecomponent such as images, text, a webpage, etc.), the example AME 108records an impression once for each occurrence of the media beingpresented, delivered, or otherwise provided to the client device 106.For streaming media (e.g., video, audio, etc.), the example AME 108measures demographics for media occurring over a period of time. Forexample, the AME 108 (e.g., via the app publisher 110 and/or the mediapublisher 120) provides beacon instructions to a client application orclient software (e.g., the OS 114, the web browser 117, the app 116,etc.) executing on the client device 106 when media is loaded at clientapplication/software 114-117. In some examples, the beacon instructionscause the client application/software 114-117 to transmit a request(e.g., a pingback message) to an impression monitoring server at regularand/or irregular intervals (e.g., every minute, every 30 seconds, every2 minutes, etc.). By monitoring and/or counting the requests occurringat intervals, the example AME 108 monitors the duration of individualimpressions of duration-based media (e.g., video, audio, etc.). Theexample AME 108 may determine the numbers of impressions (e.g., initialloads) of the duration-based media, the unique audience ofduration-based media, and/or the total duration (in units, such asseconds or minutes) of the duration-based media viewed in the numbers ofimpressions. As used herein, the term “impression information” mayinclude impressions and/or duration units. The example impressionmonitoring server 132 identifies the requests from the web browser 117and, in combination with one or more database proprietors, matches theimpression information for the media with demographics of the user ofthe web browser 117.

In some examples, a user loads (e.g., via the browser 117) a web pagefrom a web site publisher, in which the web page corresponds to aparticular 60 minute video. As a part of or in addition to the exampleweb page, the web site publisher causes the data collector 112 to send apingback message (e.g., a beacon request) to a beacon server 142 by, forexample, providing the browser 117 with beacon instructions. Forexample, when the beacon instructions are executed by the examplebrowser 117, the beacon instructions cause the data collector 112 tosend pingback messages (e.g., beacon requests, hypertext transferprotocol (HTTP) requests, pings) to the impression monitoring server 132at designated intervals (e.g., once every minute or any other suitableinterval). The example beacon instructions (or a redirect message from,for example, the impression monitoring server 132 or a databaseproprietor 104 a-b) further cause the data collector 112 to sendpingback messages or beacon requests to one or more database proprietors104 a-b that collect and/or maintain demographic information aboutusers. The database proprietor 104 a-b transmits demographic informationabout the user associated with the data collector 112 for combining orassociating with the impression determined by the impression monitoringserver 132. If the user closes the web page containing the video beforethe end of the video, the beacon instructions are stopped, and the datacollector 112 stops sending the pingback messages to the impressionmonitoring server 132. In some examples, the pingback messages includetimestamps and/or other information indicative of the locations in thevideo to which the numerous pingback messages correspond. By determininga number and/or content of the pingback messages received at theimpression monitoring server 132 from the client device 106, the exampleimpression monitoring server 132 can determine that the user watched aparticular length of the video (e.g., a portion of the video for whichpingback messages were received at the impression monitoring server132).

The client device 106 of the illustrated example executes a clientapplication/software 114-117 that is directed to a host website (e.g.,www.acme.com) from which the media 118 (e.g., audio, video, interactivemedia, streaming media, etc.) is obtained for presenting via the clientdevice 106. In the illustrated example, the media 118 (e.g.,advertisements and/or content) is tagged with identifier information(e.g., a media ID 122, a creative type ID, a placement ID, a publishersource uniform resource locator (URL), etc.) and a beacon instruction.The example beacon instruction causes the client application/software114-117 to request further beacon instructions from a beacon server 142that will instruct the client application/software 114-117 on how andwhere to send beacon requests to report impressions of the media 118.For example, the example client application/software 114-117 transmits arequest including an identification of the media 118 (e.g., the mediaidentifier 122) to the beacon server 142. The beacon server 142 thengenerates and returns beacon instructions 144 to the example clientdevice 106. Although the beacon server 142 and the impression monitoringserver 132 are shown separately, in some examples the beacon server 142and the impression monitoring server 132 are combined. In theillustrated example, beacon instructions 144 include URLs of one or moredatabase proprietors (e.g., one or more of the partner databaseproprietors 104 a-b) or any other server to which the client device 106should send beacon requests (e.g., impression requests). In someexamples, a pingback message or beacon request may be implemented as anHTTP request. However, whereas a transmitted HTTP request identifies awebpage or other resource to be downloaded, the pingback message orbeacon request includes the audience measurement information (e.g., adcampaign identification, content identifier, and/or device/useridentification information) as its payload. The server to which thepingback message or beacon request is directed is programmed to log theaudience measurement data of the pingback message or beacon request asan impression (e.g., an ad and/or content impression depending on thenature of the media tagged with the beaconing instructions). In someexamples, the beacon instructions received with the tagged media 118include the beacon instructions 144. In such examples, the clientapplication/software 114-117 does not need to request beaconinstructions 144 from a beacon server 142 because the beaconinstructions 144 are already provided in the tagged media 118.

When the beacon instructions 144 are executed by the client device 106,the beacon instructions 144 cause the client device 106 to send beaconrequests (e.g., repeatedly at designated intervals) to a remote server(e.g., the impression monitoring server 132, the media publisher 120,the database proprietors 104 a-b, or another server) specified in thebeacon instructions 144. In the illustrated example, the specifiedserver is a server of the audience measurement entity 108, namely, atthe impression monitoring server 132. The beacon instructions 144 may beimplemented using Javascript or any other types of instructions orscript executable via a client application (e.g., a web browser)including, for example, Java, HTML, etc.

The example AME 108 of FIG. 1 further includes a panel database 146 tostore panel and/or panelist information. Example panel and/or panelistinformation includes demographic data, market segment data, and deviceusage information about individual panelists and/or panelist households.The example panel database 146 may be updated by a panel data collector148 based on collection of audience information for television audiencemeasurement, radio audience measurement, online audience measurement,mobile audience measurement, and/or cross-platform (or multi-platform)audience measurement. The example panel data collector 148 may collectpanel data using the methods and apparatus disclosed in Topchy, et al.,U.S. Pat. No. 8,369,972, Thomas et al., U.S. Pat. No. 5,481,294, and/orEllis et al., U.S. Pat. No. 5,504,518. The entireties of U.S. Pat. Nos.8,369,972, 5,481,294, and 5,504,518 are incorporated herein byreference. However, any other past, present, or future techniques forcollecting panel audience measurement data may be used.

Examples that may be used to implement the system of FIG. 1 aredisclosed in U.S. patent application Ser. No. 14/127,414, filed on Aug.28, 2013, U.S. patent application Ser. No. 14/261,085, filed on Apr. 24,2014, U.S. Provisional Patent Application Ser. No. 61/952,726, filed onMar. 13, 2014, U.S. Provisional Patent Application Ser. No. 61/979,391,filed on Apr. 14, 2014, U.S. Provisional Patent Application Ser. No.61/986,784, filed on Apr. 30, 2014, U.S. Provisional Patent ApplicationSer. No. 61/991,286, filed on May 9, 2014, and U.S. Provisional PatentApplication Ser. No. 62/014,659, filed Jun. 19, 2014. The entireties ofU.S. patent application Ser. No. 14/127,414, U.S. patent applicationSer. No. 14/261,085, U.S. Provisional Patent Application Ser. No.61/952,726, U.S. Provisional Patent Application Ser. No. 61/979,391,U.S. Provisional Patent Application Ser. No. 61/986,784, U.S.Provisional Patent Application Ser. No. 61/991,286, and U.S. ProvisionalPatent Application Ser. No. 62/014,659 are incorporated by referenceherein.

Attributing Impression Information to Market Segments

The examples of FIGS. 2-6 below may be used to estimate a share of theimpression counts, the unique audience sizes, and/or the duration units,which are determined as described above with reference to FIG. 1 , thatare attributable to a market segment of interest. Because accuratemarket segment information is often not available from the databaseproprietors 104 a-b, the example methods and apparatus of FIGS. 2-6 usemarket segment information from other sources, such as audiencemeasurement panels for television, radio, and/or online audiencemeasurements. Examples disclosed below verify that the panel audiencesfrom which the market segment information is to be drawn satisfiesrequirements to enhance the reliability (e.g., precision) of theimpression and/or audience attributions. The examples may be used tocalculate impression counts, duration units, and/or unique audiencesizes attributable to the market segments using demographic groups thatsatisfy the precision thresholds (e.g., are based on audience samplesizes exceeding established thresholds).

FIG. 2 is a block diagram of an example implementation of the exampleimpression monitoring server 132 of FIG. 1 . As discussed above, theexample impression monitoring server 132 of FIG. 2 attributesimpressions to demographic groups and/or determines audience sizes ofdemographic groups. Additionally, the example impression monitoringserver 132 of FIG. 2 determines portions of impressions and/or portionsof audiences (e.g., audience members) that are attributable to one ormore designated market segments (also referred to as “market breaks”).

The example impression monitoring server 132 of FIG. 1 includes animpression collector 202, a demographics determiner 204, a precisiondeterminer 206, and a market segment calculator 208.

The example impression collector 202 of FIG. 2 receives impressionrequests from mobile devices, such as the client device 106 as describedabove with reference to FIG. 1 . The impression requests received at theimpression collector 202 are indicative of accesses to media at themobile devices. For example, the requests may include impression data130 such as one or more media IDs 122 and/or one or more device/useridentifier(s) 124 to report impressions.

The impression requests may be implemented, for example, as HTTPrequests. However, whereas a transmitted HTML request identifies awebpage or other resource to be downloaded, the impression requestincludes the audience measurement information (e.g., ad campaignidentification, a content identifier, and/or user identificationinformation) as its payload. The example impression requests are dummyHTTP requests requesting a resource (e.g., a web page) but to which aweb page is not served by the impression collector 202. The dummy HTTPrequest serves as an impression request that effectively requests theimpression collector 202 to log an impression for corresponding accessedmedia that is identified in the dummy HTTP impression request.

The example impression collector 202 of FIG. 2 sends requests fordemographic information (e.g., to the database proprietor(s) 104 a-104b). The requests for demographic information correspond to the mobiledevices that send dummy requests (e.g., to an Internet domain associatedwith the AME 108). For example, the impression collector 202 may sendone request for demographic information (e.g., to the databaseproprietor(s) 104 a-104 b) corresponding to multiple requests receivedfrom the mobile devices. Additionally or alternatively, the impressioncollector 202 may send requests for demographic information for eachrequest received from a mobile device (e.g., on a one for one basis). Inany case, the impression collector 202, in turn, receives demographicinformation corresponding to the mobile devices e.g., from the databaseproprietor(s) 104 a-104 b) and logs the demographic information inassociation with corresponding ones of the logged impressions.

The example demographics determiner 204 of FIG. 2 determines a number ofmedia impressions that occurred on mobile devices and that areattributable to a demographic group based on the information collectedby the impression collector 202. For example, the demographicsdeterminer 204 determines the number of media impressions attributableto a given demographic group based on the demographic data provided by adatabase proprietor (e.g., the database proprietor 104 a of FIG. 1 ).For example, the demographics determiner 204 determines mediaimpressions that are attributable to a demographic group based on theuser information 102 a received from the database proprietor 104 a bycorrecting the data for any bias (e.g., misattribution bias thatincorrectly attributes to one demographic group one or more impressionsthat are correctly attributable to another demographic group,non-coverage bias that corrects for the fact that not all persons thatcause impressions are recognizable by the database proprietor 104 a,etc.) and/or by scaling the corrected user information to match anobserved number of impressions for the media. Example methods andapparatus that may be used to implement the demographics determiner 204are disclosed in U.S. patent application Ser. No. 14/560,947, filed Dec.4, 2014. The entirety of U.S. patent application Ser. No. 14/560,947 isincorporated by reference herein.

The example precision determiner 206 of FIG. 2 determines whether thesize of a panel audience results in an unacceptable precision (e.g., asample size smaller than a threshold sample size) when used to estimatethe number of impressions attributable to a particular market segment.For example, the precision determiner 206 determines whether a size of apanel audience that corresponds to a demographic group of interest(e.g., there are X people in the panel that fall into the male, ages35-39 (M35-39) demographic group) satisfies a threshold. In someexamples, the panel audience includes a set of panelists in an audiencemeasurement panel maintained by an audience measurement entity (e.g.,the AME 108) of FIG. 1 . In the example of FIG. 2 , the precisiondeterminer 206 compares the size of the panel audience to a thresholdsize that is calculated to provide an lower acceptable sample size forattributions of impression counts, duration units, and/or audience sizesto demographic groups and/or market segments.

When the precision determiner 206 determines that the size of the panelaudience (that corresponds to the demographic group of interest) doesnot satisfy the threshold at a higher level of granularity (e.g., thefirst level), the example precision determiner 206 determines whetherthe size of a second, larger audience at a lower level of granularity(e.g., the second level, the third level, etc.) satisfies the threshold.In particular, the precision determiner 206 uses as the second audiencea larger set of panelists from the audience measurement panel thatincludes the first set of panelists plus additional panelists thatcorrespond to a larger (e.g., less granular) demographic group. Forexample, if the demographic group of the first set was an M35-39 (male,ages 35-39) demographic group, the precision determiner 206 may createthe second set by widening the age demographic to use panel audiencepanelists in the group M35-54 (male, ages 35-54). Alternatively, theprecision determiner 206 may widen the gender category to includepersons (i.e., male and female) ages 35-39 in the second group.Alternatively, the precision determiner 206 may widen both the genderand the age categories such that the second set of panelists are thosepanelists who are persons of either gender and are ages 35-54. In otherwords, the precision determiner 206 selects the second set of panelistshaving less granular demographics panel audience than the first group ofpanelists. The first set of panelists is a subset of the second set ofpanelists. The example precision determiner 206 may generate any numberof demographic granularity levels (e.g., 2, 3, 4, or more), testingincreasingly larger sets of panelists until the precision determiner 206identifies a set of panelists that satisfies the threshold.

In some examples, precision determiner 206 includes non-demographicbased requirements in addition to the panel audience size, such as arequirement to have a certain number of mobile devices and/or type(s) ofmobile devices present in the household of the audience members. Suchrequirements may be instituted to improve the representation of theoverall population by the panel audience. In such examples, an audiencemember may be excluded from the panel audience (referred to as a set ofpanelists above) if the audience member and/or the household of theaudience member do not meet the non-demographic based requirements. Theprecision determiner 206 determines whether the panel audience for ademographic group, excluding those panel audience members that are inthe demographic group but do not meet the non-demographic basedcriteria, satisfies the threshold (e.g., is at least a minimum number ofaudience members). If not, the precision determiner 206 may cause thedemographics determiner 204 to select a panel audience for a demographicgroup that includes a larger number of panel audience members, asdiscussed in more detail below.

The example market segment calculator 208 of FIG. 2 calculates numbersof impressions that are attributable to a market segment. The examplemarket segment calculator 208 determines the numbers of impressions forthe market segment of interest for individual demographic groups. Forexample, if the market segment of interest is persons having a householdincome between $50,000 and $59,999 (e.g., $50 k-$59.9 k), the examplemarket segment calculator 208 of the illustrated example determines theimpressions attributable to each of the demographic groups persons andthe proportion of persons in each of the demographics groups who have ahousehold income between $50 k-$59.9 k in the highest-granularity panelaudience that has at least the lower (e.g., minimum) acceptable samplesize. Using the female, ages 21-24 (F21-24) demographic group as anexample, the market segment calculator 208 determines a number ofimpressions attributable to the F21-24 demographic group, determineswhich granularity level has a panel size of least the threshold size(e.g., the F21-24 demographic group, the F21-30 demographic group, orthe Persons, 2-99 demographic group), and calculates a number ofimpressions attributable to persons in the F21-24 demographic group whohave a household income between $50 k-$59.9 k based on the impressionsattributable to the F21-24 demographic group and the proportion ofpersons at the determined granularity level who have a household incomebetween $50 k-$59.9 k.

In some examples, such as when a higher-granularity demographic levelpanel audience does not have enough panelists to result in an acceptablesample size in the calculation of attributable impressions, the marketsegment calculator 208 calculates the portion of the media impressionsthat are attributable to the market segment and the demographic group bymultiplying a) the proportion of the panel audience at alower-granularity demographic level that includes the panel audience atthe higher-granularity demographic level and that belongs to the marketsegment and b) a number of impressions attributable to the demographicgroup at the highest-granularity demographic level. For example, if themarket segment calculator 208 determines that the F21-24 panel audience(e.g., at highest granularity level) would not result in an acceptablesample size for determining the impressions attributable to the marketsegment of interest and the F21-24 demographic group, the market segmentcalculator 208 selects a demographic group at the next-highestgranularity level that includes the F21-24 demographic group, such asthe F21-30 demographic group. The market segment calculator 208 thencalculates the portion of the media impressions for the F21-24attributable to the market segment of interest by multiplying a) theproportion of persons in the F21-30 panel audience who belong to themarket segment of interest and b) the media impressions attributable tothe F21-24 panel audience. If the F21-30 panel audience also does notprovide an acceptable sample size, the example market segment calculator208 may repeat the calculation using the next-highest granularitydemographic level to determine the proportion of the panel audience thatbelongs to the market segment of interest, while also using the mediaimpressions attributable to the F21-24 panel audience.

The example market segment calculator 208 determines the total audiencesize (e.g., not limited to the panel audience) for each demographicgroup based on, for example, information obtained from a databaseproprietor (e.g., the database proprietor 104 a of FIG. 1 ) and a numberof media impressions counted at the impression collector 202. Exampledemographic information that may be used to calculate the total audiencesize includes counts of persons identified by the database proprietor104 a in each demographic group, and the number of impressionsattributed to each of the demographic groups by the database proprietor104 a. In some examples, the market segment calculator 208 calculatesthe portion of the media impressions attributable to a demographic groupand a market segment of interest by multiplying an impression frequencydetermined from the database proprietor 104 a for the demographic groupby the total audience (e.g., number of audience members) that belongs toboth the market segment and the demographic group.

In the example of FIG. 2 , the precision determiner 206 selects thehighest-granularity level panel audience to be used by the marketsegment calculator 208 for a demographic group when the size of thepanel audience for that demographic group satisfies a sample sizethreshold that corresponds to an acceptable precision. When thehighest-granularity level panel audience for a demographic group doesnot satisfy the threshold, the example precision determiner 206 selectsa panel audience at a lower granularity level to be used by the marketsegment calculator 208, based on the level having the highestdemographic group granularity at which the panel audience size satisfiesthe threshold. For example, when the precision determiner 206 determinesthat the size of the panel audience at the second-highest granularitylevel (e.g., F21-30) satisfies the threshold, the example market segmentcalculator 208 calculates the portion of the media impressions that areattributable to the market segment of interest and to the demographicgroup (e.g., F21-30, income $50 k-$59.9 k) based on a portion of thepanel audience in the demographic group at the second-highestgranularity level (e.g., F21-30) that belongs to the market segment(e.g., income $50 k-$59.9 k).

The example precision determiner 206 selects the highest granularitylevel for each demographic group at which the panel audience satisfiesthe threshold, regardless of whether the precision determiner 206selects a lower-granularity level for other demographic groups (e.g.,where the selected lower-granularity level may include other demographicgroups for which the highest granularity level may be selected). Forexample, the precision determiner 206 may determine that, for a M25-29demographic group, a lower-granularity level “persons 21-34” panelaudience is to be used to achieve satisfactory precision. However,rather than using the “persons 21-34” demographic group for each of thedemographic groups falling within the “persons 21-34” lower-granularitylevel demographic group, the example precision determiner 206 selectsthe highest-granularity level demographic groups for the demographicgroups for which the corresponding panel audience satisfies thethreshold (e.g., the M21-24, M30-34, F21-24, F25-29, and F30-34demographic groups).

Table 1 below illustrates an example approach for estimating marketsection audiences by device type, and in total (across device types, andacross TV households and Cross-Platform Homes (CPH)). The example marketsegment calculator 208 of FIG. 2 may use the inputs, outputs, and/orcomputations shown and described below with reference to Table 2 tocalculate impression counts, duration units, and/or audience sizesassociated with a market segment of interest.

TABLE 2 Example Approach for Estimating Market Segment Audiences forMobile Device Impressions Detailed Simplified Reference ReferenceDefinition/Computation P_(db) A Panel audience size (units) for d^(th)demo category, b^(th) market segment. Input. P_(d) B Panel audience size(units) for d^(th) demo category. Input. C_(dt) C Calibrated censusaudience size (units) for d^(th) demo category, t^(th) mobile devicetype. Input. D_(dbt) D Mobile audience size (units) for d^(th) democategory, b^(th) market break, t^(th) mobile device type.$D = {{C \times \frac{A}{B}\mspace{14mu}{or}\mspace{14mu} D_{dbt}} = {C_{dt} \times \frac{P_{db}}{P_{d}}}}$D_(db) E Mobile audience size (units) for d^(th) demo category, b^(th)market egment (E = sum of D across device types, or$\left. {D_{db} = {\sum\limits_{f}D_{dbf}}} \right)$ T_(db) F Existingaudience size (units) for d^(th) demo category, b^(th) market segment.The composition of this audience may vary by service and/or client.Input. S_(db) G TV + PC + Mobile audience size (units) for d^(th) democategory, b^(th) market segment. G = F + E = T_(db) + D_(db)

In Table 2 above, A (or P_(db)) is a panel audience for the d^(th)demographic group (e.g., females of ages 18-21 (F18-21), females of ages18-30 (F18-30), persons of age 2 and over, etc.) and the b^(th) marketsegment (e.g., household income $50,000-59,999). In Table 2 above, B (orP_(d)) is a panel audience for the d^(th) demographic group. Therefore,the ratio A/B is the portion (e.g., percentage or fraction) of thed^(th) demographic group made up by the b^(th) market segment. A and Babove are obtained from an audience panel (e.g., panel-based), such as astatistically-selected television audience panel, astatistically-selected PC audience panel, and/or a statisticallyselected radio audience panel maintained by an audience measuremententity such as The Nielsen Company. The audience may be, for example,the number of persons in the panel audience that fit the criteria (e.g.,the d^(th) demographic group, the b^(th) market segment, etc.).

The panel audience A (or P_(db)) and the panel audience B (or P_(d)) areobtained from the demographics determiner 204 based on a demographicgroup selected by the precision determiner 206 (e.g., at a level thatresults in a satisfactory precision). For example, when the precisiondeterminer 206 selects a demographic group level (e.g., a granularitylevel), the example demographics determiner 204 determines a number ofpersons in the panel audience that are known to be in the d^(th)demographic group (e.g., the demographic group of interest, alower-granularity-level demographic group that includes the demographicgroup of interest, etc.) and the b^(th) market segment. The examplemarket segment calculator 208 obtains A and B from the panel database146 based on a demographic group selected by the precision determiner206.

In Table 2 above, C (or C_(dt)) is a calibrated census audience size (orimpression counts) for the d^(th) demographic group and the t^(th)device type out of n device types (e.g., device types t₁, t₂, . . .t_(n)). The example demographics determiner 204 of FIG. 2 determines thecalibrated census audience size (or impression counts) C by attributingmedia audience members and/or impressions to demographic groups basedon, for example, demographic information received from a databaseproprietor (e.g., the database proprietor 104 a of FIG. 1 ) to whichpeople have provided (e.g., self-reported) such demographic information.The example precision determiner 206 indicates the demographic group dto the demographics determiner 204, based on the demographic group dused to obtain A and B.

In some examples, the demographics determiner 204 converts the mediaimpression count and/or the duration unit count to a unique audiencesize using a frequency measure determined for the d^(th) demographicgroup (e.g., by the database proprietor, by the audience measuremententity, etc.). As used herein, frequency is defined to refer to theratio of an impression count to a unique audience size. Therefore,frequency may be considered an average number of impressions per personin the audience. A value for C may be a number of media impressionsobtained using the example methods and apparatus disclosed in U.S.patent application Ser. No. 14/560,947.

In Table 2 above, D (or D_(dbt)) is a calculated value representing amobile audience size (or number of impressions) for the d^(th)demographic group, the b^(th) market segment, and the t^(th) devicetype. The example market segment calculator 208 of FIG. 2 calculates Das

$D = {C \times \frac{A}{B}{\left( {{{or}\mspace{14mu} D_{dbt}} = {C_{dt} \times \frac{P_{db}}{P_{d}}}} \right).}}$

In Table 2 above, E (or D_(db)) is a mobile audience size (or number ofimpressions) for the d^(th) demographic group and the b^(th) marketsegment. The example market segment calculator 208 calculates E as thesum of D (or D_(dbt)) for all of the device types t₁-t_(n). For example,the market segment calculator 208 may calculate E using the formula

$E = {\sum\limits_{t}{{D\left( {{{or}\mspace{14mu} D_{db}} = {\sum\limits_{t}D_{dbt}}} \right)}.}}$

In Table 2 above, F (or T_(db)) is the existing audience size for thed^(th) demographic group and the b^(th) market segment. The existingaudience size refers to an audience size for media presented using adifferent platform than the platform represented by D in Table 2 above.For example, the market segment calculator 208 obtains the existingaudience F as an audience for the media of interest for devices notincluded in the set of device types t₁-t_(n). For example, if the set ofdevice types t₁-t_(n) include mobile device types such as smartphones,tablet computers, and/or portable media players, the existing audience Fmay reflect audiences of device types such as desktop computers,televisions, and/or radios. Existing audience sizes may be differentbased on the particular service (e.g., national vs local service). Forexample, in national reporting, the existing audience size may includeTV-only audience (or radio only), or may include combined TV and PC (orradio and PC) audiences depending on the networks' respectiveparticipation in extended access programs that monitor media access ondevices such as personal computers. As an example for local reporting,existing audience sizes may only include TV audiences (or radioaudiences).

Example methods and apparatus for determining an audience for computingdevices are disclosed in U.S. Pat. No. 6,108,637 to Blumenau. Examplemethods and apparatus for determining an audience for television and/orradio are described in U.S. Pat. No. 5,481,294 to Thomas et al. and/orU.S. Pat. No. 5,504,518 to Ellis et al. The entireties of U.S. Pat. Nos.6,108,637, 5,481,294, and 5,504,518 are incorporated herein byreference.

In Table 2 above, G is a total of the mobile audience size (e.g., E orD_(db)) and existing audience size (e.g., F or T_(db)) for the marketsegment for the d^(th) demographic group and the b^(th) market segment.In the example above, the market segment calculator 208 calculates Gusing the equation G=F+E=T_(db)+D_(db). Therefore, the above example canprovide an audience for a market segment of interest for mediaimpressions occurring on mobile devices and/or for total accesses of themedia across devices (e.g., mobile devices, non-mobile computingdevices, television, radio, etc.). The example market segment calculator208 may calculate the audience for the market segment of interest in oneor more selected demographic groups using the panel audiences selectedby the precision determiner 206 for each of the selected demographicgroups. Additionally or alternatively, the market segment calculator 208may sum the audiences across multiple demographic groups to determinethe audience for the entire market segment of interest.

As discussed above, the example precision determiner 206 determines thesample size associated with the panel-based market segment calculationsto determine whether the sample size traverses a threshold. The datasource of the panel-based share (e.g., the data source, such as atelevision audience measurement panel, used to obtain A and B in Table 2above) and the demographic granularity level at which the share iscomputed, are based on the numbers of viewers and availability of thepanel data. Availability of panel data refers to whether audiencemeasurement panel data can be obtained from a desired source for ademographic group. The demographic granularity level refers to thegranularity of the demographic groups used to determine the marketsegment share. For example, the females of ages 18-21, females of ages21-24, females of ages 24-27, and females of ages 28-30 demographicgroups at a first demographic granularity level all have a highergranularity than a females of ages 18-30 demographic group at a seconddemographic granularity level and/or a persons of ages 2+ (e.g., maleand female, ages 2 and up) demographic group at a third demographicgranularity level. Table 3 below illustrates example sets of demographicgroups at three different demographic granularity levels.

TABLE 3 Example Granularity Levels Demographic Granularity Levels 1-3Demographic Demographic Demographic Granularity Granularity GranularityLevel 1 Level 2 Level 3 Female, age 2-5 Children, age 2-11 Persons, age2+ Female, age 6-8 Female, age 9-11 Female, age 12-14 Teens, age 12-17Female, age 15-17 Female, age 18-20 Persons, age 18-24 Female, age 21-24Female, age 25-29 Persons, age 25-34 Female, age 30-34 Female, age 35-39Persons, age 35-54 Female, age 40-44 Female, age 45-49 Female, age 50-54Female, age 55-64 Persons, age 55+ Female, age 65+ Male, age 2-5Children, age 2-11 Male, age 6-8 Male, age 9-11 Male, age 12-14 Teens,age 12-17 Male, age 15-17 Male, age 18-20 Persons, age 18-24 Male, age21-24 Male, age 25-29 Persons, age 25-34 Male, age 30-34 Male, age 35-39Persons, age 35-54 Male, age 40-44 Male, age 45-49 Male, age 50-54 Male,age 55-64 Persons, age 55+ Male, age 65+

In the example of Table 3 above, each granularity level is a surjectionof the immediately preceding level (e.g., Demographic Granularity Level1 precedes Demographic Granularity Level 2 in the example Table 3above). In other words, each demographic group at one demographicgranularity level in Table 3 above (e.g., the female, ages 12-14demographic group in Demographic Granularity Level 1) fits into (or ismapped to) a demographic group at each of the higher demographicgranularity levels in Table 3 above (e.g., Teens, ages 12-17 inDemographic Granularity Level 2, Persons 2+ in Demographic GranularityLevel 3).

At each demographic granularity level in Table 3 above, the marketsegment calculator 208 determines the market segment share ofimpressions and/or audience members based on the ratio of market segmentprojected audience (or impressions) (e.g., A in Table 1 above) to totalprojected audience (or impressions) (e.g., B in Table 1 above).

In some examples, the precision determiner 206 uses a hierarchicalapproach so that the demographic granularity level expected to be mosthighly correlated with mobile viewing by the market segment isconsidered first. Thus, the example market segment calculator 208calculates the mobile audience size (or impressions) E for the d^(th)demographic group and the b^(th) market segment according to Table 1above for the demographic groups d at Demographic Granularity Level 1 ofTable 3 above. For example, the example demographics determiner 204provides the market segment projected audience A and the total projectedaudience B of Table 1 above are obtained for each of the 30 demographicgroups at Demographic Granularity Level 1 of Table 3 above. Thecalibrated census audience size C of Table 1 above is also obtained foreach of the 30 demographic groups d at Demographic Granularity Level 1of Table 3 above. The example market segment calculator 208 calculatesthe mobile audience size D of Table 1 for each of the 30 demographicgroups d at Demographic Granularity Level 1 of Table 3 above. The marketsegment calculator 208 calculates the mobile audience size (or number ofimpressions) E of Table 1 for each of the 30 demographic groups d atDemographic Granularity Level 1 of Table 3 above.

In some examples, if the precision determiner 206 determines that thethreshold for the panel audience B of Table 1 above (e.g., a minimumaudience) is not satisfied for one or more of the demographic groups ata particular demographic granularity level, the example market segmentcalculator 208 uses another demographic granularity level (e.g., a lessgranular level having more panelists) to calculate the impressionsand/or audience for the market segment. For example, the precisiondeterminer 206 may compare the panel audience B to the threshold priorto the market segment calculator 208 calculating the mobile audiencesize (or number of impressions) E at that demographic granularity level.

For example, if the precision determiner 206 determines that a firstdemographic group (e.g., female, ages 18-20) at Demographic GranularityLevel 1 of Table 3 above has a panel audience (e.g., B of Table 1 above)of fewer than an example threshold of 30 people, then the precisiondeterminer 206 determines whether the next demographic granularity level(e.g., Demographic Granularity Level 2 of Table 3 above) has a panelaudience of fewer than the example threshold. In this example, theprecision determiner 206 would determine whether the Persons, ages 18-24demographic group audience has at least 30 people. If the Persons, ages18-24 demographic group audience has at least 30 people, the exampleprecision determiner 206 instructs the market segment calculator to usethe Persons, ages 18-24 demographic group to determine the marketsegment projected audience A and the total projected audience B tocalculate the mobile audience (or number of impressions) E for thefemale, ages 18-20 demographic group. The market segment calculator 208would then obtain the panel audience A for the Persons, ages 18-24demographic group and the panel audience B for the Persons, ages 18-24demographic group from the panel database 146.

In some examples, the Demographic Granularity Levels and demographicgroups in each of the levels may be defined using an establishedaudience panel such as the Nielsen National TV Ratings panel. However,other panels may be used that have a correlation between the panelmember behavior and mobile device user behavior that is higher than, forexample, the correlation between the Nielsen National TV Ratings paneland mobile device user behavior.

In some examples, the market segment calculator 208 calculates separateshares for the same market segment for different time-shifted viewingstreams. A time-shifted viewing stream refers to media that is accessedfrom a source of time-shifted media access, such as a particular website, a particular service, or a particular mobile device application.Time-shifted refers to accessing archived or recorded media at a latertime and/or date relative to the time/date at which the media wasbroadcast or distributed for real-time access during a scheduledtime/date. In some other examples, the market segment calculator 208calculates a single share for the market segment based on a singlestream, and the single share is then utilized for all measuredtime-shifted viewing streams.

Table 4 below illustrates another example set of granularity levels thatmay be used by the example market segment calculator 208 to calculate ashare of impressions and/or audience for a market segment. The examplegranularity levels of Table 4 below may be used to measure marketsegment share for, for example, local media telecasts (as opposed tonational media telecasts) on local stations (e.g., national networkaffiliates).

TABLE 4 Alternative Example Granularity Levels Local GranularityHousehold-level Level Device Requirement Demo Tuning Segment 1 All TVpanel homes BB Day/Station/¼ hour 2 All TV panel homes Demo (6)Day/Station/¼ hour 3 All TV panel homes P2+ Day/Station/¼ hour 4 All TVpanel homes BB Day/Station/½ hour 5 All TV panel homes Demo (6)Day/Station/½ hour 6 All TV panel homes P2+ Day/Station/½ hour 7 All TVpanel homes BB Day/Station/1 hour 8 All TV panel homes Demo (6)Day/Station/1 hour 9 All TV panel homes P2+ Day/Station/1 hour

In the example of Table 4 above, BB refers to a set of “building block”demographic categories, such as the set of national building blockdemographic categories (e.g., age/gender groups) used in the NielsenNational TV Ratings panel. The BB demographic groups are an example of a“most granular” set of demographic groups in the granularity levels, andmay be replaced with other sets of demographic groups based on paneldata availability. In the example of Table 4 above, Demo (6) refers tothe example demographic groups in Demographic Granularity Level 2 ofTable 3 above, including: 1) Children, ages 2-11; 2) Teens, ages 12-17;3) Persons, ages 18-24; 4) Persons, ages 25-34; 5) Persons, ages 35-54;and 6) Persons, ages 55+. In the example of Table 4 above, theDay/Station/Time period (e.g., ¼ hour, ½ hour, 1 hour) refers to thelocal station, day, and day-part (e.g., a designated ¼ hour, adesignated ½ hour, a designated hour, etc.) from which the panelaudience is estimated or determined. For example, an audience measuredfrom a panel on a particular ¼ hour (e.g., 5:00 P.M.-5:15 P.M., etc.) ofa particular day (e.g., Friday, Friday, Nov. 28, 2014, etc.) from aparticular station (e.g., a local CBS affiliate station) may be used.

Using the example granularity levels of Table 4, the example precisiondeterminer 206 first tests the panel audience size (e.g., B of Table 1)at granularity level 1 (e.g., BB demographic groups, with the panelaudience determined from the day/station/¼ hour corresponding to themedia impression) to determine whether each of the example demographicgroups in BB have at least a threshold panel audience (e.g., whether thepanel audience B of Table 1 above is greater than a threshold audiencesize). If not all of the demographic groups (BB) have at least thethreshold panel audience, the example precision determiner 206 tests thepanel audience size at granularity level 2 (e.g., Demo (6) demographicgroups, with the panel audience determined from the day/station/¼ hourcorresponding to the media impression).

If the third example granularity level of Table 4 above (e.g., personsof ages 2+, with the panel audience determined from the day/station/¼hour corresponding to the media impression) does not have at least athreshold panel audience size, the example granularity level 4 is used,which increases the day-part time frame to ½ hour and returns to testthe demographic groups at the highest level of granularity (e.g., the BBdemographic groups).

The example precision determiner 206 progresses through the panelaudience size at each subsequent granularity level (e.g., levels 1-9 ofTable 4 above) until the precision determiner 206 determines that thegranularity level has a panel audience size that meets the threshold forall of the demographic groups at the granularity level. When theprecision determiner 206 identifies a granularity level that has a panelaudience size that meets the threshold for all of the demographicgroups, the example market segment calculator 208 obtains the marketsegment projected audience A, the total projected audience B, and thecalibrated census audience size C of Table 1 above for the demographicgroups at the identified granularity level and the market segment ofinterest.

For example, if all of the demographic groups in Demo (6) of Table 4satisfy the threshold for the panel audience size at the ¼ hourday-part, the example market segment calculator 208 obtains 6 sets ofdata for each of the market segment projected audience A, the totalprojected audience B, and the calibrated census audience size C. Theexample market segment calculator 208 calculates values for the mobileaudience (or number of impressions) E for each of the six demographicgroups as described above. In some examples, the market segmentcalculator 208 obtains multiple values of the calibrated census audiencesize C and/or multiple values of the mobile audience size (or number ofimpressions) D are calculated for each demographic group d for themultiple device types t of Table 1 above. For example, a first value ofthe calibrated census audience size C may be obtained for a first devicetype and a second value of the calibrated census audience size C may beobtained for a second device type.

FIG. 3 illustrates an example estimation of a mobile device audience asdescribed in Table 1 that may be performed by the example market segmentcalculator 208 for example demographic categories (e.g., agers 12-17,18-24, 25-34, and 35+), example device types (e.g., smartphones (SP) andtablets/personal media players (PMPs)), and an example market segment(e.g., household income $50,000-59,999). A first input table 302includes ratios of A/B (e.g., based on A and B of Table 1 above) forfour example age-based demographic categories (e.g., agers 12-17, 18-24,25-34, and 35+) of a TV audience. In the example table 302, the ratioA/B used to calculate the mobile audience size (or number ofimpressions) D in Table 1 above for the d^(th) demographic group and theb^(th) market segment is received instead of separate data elements Aand B.

A second input table 304 includes impressions for the example age-baseddemographic categories and the example device type of “smartphone.”Similarly, a third input table 306 includes impressions for the exampleage-based demographic categories and the example device type of“tablet/personal media player (PMP).” The input tables 304, 306 of FIG.3 correspond to the calibrated census audience size C input data ofTable 1 above. The example input tables 304, 306 may be obtained fromthe demographics determiner 204 based on the impressions collected bythe impressions collector 202 and/or demographic information receivedfrom the partner database proprietor 104 a of FIG. 2 .

Using the first input table 302 and the second input table 304, theexample market segment calculator 208 calculates the impressions (D1)for the smartphone type and for the example market segment to generatethe output table 308 for the smartphone device type. The values in theoutput table 308 correspond to the number of impressions (or audiencesize) D in Table 1 above. For example, the market segment calculator 208multiplies the 100 impressions (C1) in the ages 12-17 demographic groupin the table 304 by 0.4 (e.g., the ratio A/B) in the ages 12-17demographic group in table 302 to equal 40 impressions (D1) in the table308.

Similarly, using the first input table 302 and the third input table306, the example market segment calculator 208 calculates theimpressions (D2) for the tablet/personal media player device type forthe market segment to generate table 310 for the tablet/personal mediaplayer device type. For example, the market segment calculator 208multiplies the 200 impressions (C2) in the ages 12-17 demographic groupin the table 306 by 0.4 (e.g., the ratio A/B) in the ages 12-17demographic group in table 302 to equal 80 impressions (D2) in the table310.

The example output tables 308, 310 of FIG. 3 also include correspondingnumbers of impressions for market segments other than the selectedmarket segment (e.g., as a consequence of computing the numbers ofimpressions for the market segment of interest).

The example market segment calculator 208 further computes theimpression counts for each of the demographic groups for all of thedevice types (e.g., E of Table 1) by summing the impressions (D1+D2) foreach of the device types per demographic group. The output of thecalculation of E is shown in table 312 of FIG. 3 . For example, thetotal impression counts (E) for all device types for the 12-17demographic group and the $50,000-59,999 market segment is the sum ofthe impressions for the ages 12-17 demographic group and the$50,000-59,999 market segment for the smartphone device type (e.g.,output table 308, or D1) and the impressions for the ages 12-17demographic group and the $50,000-59,999 market segment for thetablet/portable media player device type (e.g., output table 310, orD2).

In some cases, some demographic groups at a particular granularity levelmay have at least the threshold panel audience while others of thedemographic groups at that granularity level do not have the thresholdpanel audience. In some examples, each demographic group uses the panelaudience size (e.g., A and/or B) for the applicable demographic grouphaving the highest granularity. Using the example of Table 3 above, allof the example demographic groups female of ages 25-29, female of ages30-34, male of ages 25-29, and male of ages 0-34 are in the DemographicGranularity Level 1 and also map to the demographic group Persons ofages 25-34 in Demographic Granularity Level 2. Assume, for example, eachof the demographic groups female of ages 25-29, female of ages 30-34,and male of ages 25-29 have a panel audience size (e.g., B of Table 1above) that is less than the threshold. Also assume that the exampledemographic group male of ages 30-34 has a panel audience size that isgreater than the threshold. For the example demographic groups female ofages 25-29, female of ages 30-34, male of ages 25-29, the sample size isinsufficient at Demographic Granularity Level 1 to provide an acceptableprecision of a resulting mobile device audience if the panel audiencesize is used for those demographic groups. Therefore, the panel audiencefor the Persons of ages 25-34 demographic group is used to calculate themobile device audience (e.g., E of Table 1 above) for the demographicgroups female of ages 25-29, female of ages 30-34, male of ages 25-29.However, because the panel audience size for the male of ages 30-34demographic group is greater than the threshold, the panel audience sizefor the male of ages 30-34 group is used (instead of the Persons of ages25-34 demographic group used for the other demographic groups) tocalculate the mobile device audience (e.g., E of Table 1 above).

Using the less granular Demographic Granularity Level 2 to calculate themobile device audience for the demographic groups female of ages 25-29,female of ages 30-34, male of ages 25-29, as in the example above, couldresult in a higher bias or error for the calculated mobile deviceaudience for these groups (e.g., due to less correlation between thepanel audience behavior and the mobile device user behavior), butincreases the precision. In contrast, because the sample size of theaudience in the male of ages 30-34 demographic group is sufficientlylarge, the mobile device audience for the male of ages 30-34 demographicgroup has a lower bias while also having a precision within definedlimits.

While an example manner of implementing the impression monitoring server132 of FIG. 1 is illustrated in FIG. 2 , one or more of the elements,processes and/or devices illustrated in FIG. 2 may be combined, divided,re-arranged, omitted, eliminated and/or implemented in any other way.Further, the example impression collector 202, the example demographicsdeterminer 204, the example precision determiner 206, the example marketsegment calculator 208 and/or, more generally, the example impressionmonitoring server 132 of FIG. 2 may be implemented by hardware,software, firmware and/or any combination of hardware, software and/orfirmware. Thus, for example, any of the example impression collector202, the example demographics determiner 204, the example precisiondeterminer 206, the example market segment calculator 208 and/or, moregenerally, the example impression monitoring server 132 could beimplemented by one or more analog or digital circuit(s), logic circuits,programmable processor(s), application specific integrated circuit(s)(ASIC(s)), programmable logic device(s) (PLD(s)) and/or fieldprogrammable logic device(s) (FPLD(s)). When reading any of theapparatus or system claims of this patent to cover a purely softwareand/or firmware implementation, at least one of the example impressioncollector 202, the example demographics determiner 204, the exampleprecision determiner 206, and/or the example market segment calculator208 is/are hereby expressly defined to include a tangible computerreadable storage device or storage disk such as a memory, a digitalversatile disk (DVD), a compact disk (CD), a Blu-ray disk, etc. storingthe software and/or firmware. Further still, the example impressionmonitoring server 132 of FIG. 1 may include one or more elements,processes and/or devices in addition to, or instead of, thoseillustrated in FIG. 2 , and/or may include more than one of any or allof the illustrated elements, processes and devices.

Flowcharts representative of example machine readable instructions forimplementing the impression monitoring server 132 of FIGS. 1 and/or 2are shown in FIGS. 4, 5, and 6 . In this example, the machine readableinstructions comprise program(s) for execution by a processor such asthe processor 712 shown in the example processor platform 700 discussedbelow in connection with FIG. 7 . The program(s) may be embodied insoftware stored on a tangible computer readable storage medium such as aCD-ROM, a floppy disk, a hard drive, a digital versatile disk (DVD), aBlu-ray disk, or a memory associated with the processor 712, but theentire program(s) and/or parts thereof could alternatively be executedby a device other than the processor 712 and/or embodied in firmware ordedicated hardware. Further, although the example program(s) aredescribed with reference to the flowcharts illustrated in FIGS. 4, 5,and 6 , many other methods of implementing the example impressionmonitoring server 132 may alternatively be used. For example, the orderof execution of the blocks may be changed, and/or some of the blocksdescribed may be changed, eliminated, or combined.

As mentioned above, the example processes of FIGS. 4, 5 , and/or 6 maybe implemented using coded instructions (e.g., computer and/or machinereadable instructions) stored on a tangible computer readable storagemedium such as a hard disk drive, a flash memory, a read-only memory(ROM), a compact disk (CD), a digital versatile disk (DVD), a cache, arandom-access memory (RAM) and/or any other storage device or storagedisk in which information is stored for any duration (e.g., for extendedtime periods, permanently, for brief instances, for temporarilybuffering, and/or for caching of the information). As used herein, theterm tangible computer readable storage medium is expressly defined toinclude any type of computer readable storage device and/or storage diskand to exclude propagating signals and transmission media. As usedherein, “tangible computer readable storage medium” and “tangiblemachine readable storage medium” are used interchangeably. Additionallyor alternatively, the example processes of FIGS. 4, 5 , and/or 6 may beimplemented using coded instructions (e.g., computer and/or machinereadable instructions) stored on a non-transitory computer and/ormachine readable medium such as a hard disk drive, a flash memory, aread-only memory, a compact disk, a digital versatile disk, a cache, arandom-access memory and/or any other storage device or storage disk inwhich information is stored for any duration (e.g., for extended timeperiods, permanently, for brief instances, for temporarily buffering,and/or for caching of the information). As used herein, the termnon-transitory computer readable medium is expressly defined to includeany type of computer readable storage device and/or storage disk and toexclude propagating signals and transmission media. As used herein, whenthe phrase “at least” is used as the transition term in a preamble of aclaim, it is open-ended in the same manner as the term “comprising” isopen ended.

FIG. 4 is a flowchart representative of example computer readableinstructions 400 which may be executed to implement the exampleimpression monitoring server 132 of FIGS. 1 and/or 2 to calculate ashare of a market segment of interest by selecting a demographicgranularity level based on comparing the panel audience size for thedemographic granularity level to a threshold. In the example of FIG. 4 ,the precision determiner 206 of FIG. 2 selects a lowest granularitylevel that satisfies the sample size threshold for each demographicgroup, regardless of whether a higher level is used for anotherdemographic group.

The example precision determiner 206 of FIG. 2 selects a market segments of interest (block 402). For example, the selected market segment ofinterest may correspond to a particular demographic group, based on oneor more demographic characteristics such as household income range,ethnicity, etc. The example precision determiner 206 selects ademographic group d at the lowest granularity level (block 404). Forexample, the selected demographic group may be the female, ages 2-5demographic group of Table 3 above or a first demographic group of thebuilding block demographic groups of Table 4 above. The exampleprecision determiner 206 selects a demographic granularity level (block406). In the example of FIG. 4 , the precision determiner 206 firstselects a lowest demographic granularity level for a selecteddemographic group d, and each subsequent iteration of block 406 for aselected demographic group uses a next-lowest demographic granularitylevel. For example, the demographic granularity level may be theDemographic Granularity Level 1 of Table 3 above or the DemographicGranularity Level 1 of Table 4 above.

The example precision determiner 206 determines whether the panelaudience size (e.g., B of Table 1 above) at the selected demographicgranularity level for the selected demographic group is less than athreshold (block 408). For example, the threshold may be a minimumsample size (e.g., a minimum number of people in an established audiencemeasurement panel who belong to the demographic group audience) for thedemographic group in the panel.

When the panel audience size is not less than (e.g., satisfies) thethreshold (block 408), the example precision determiner 206 sets theselected demographic group d to use the panel audience at the selecteddemographic granularity level for attributing audience and/orimpressions to a market segment s (block 410). In the illustratedexample, the market segment s is the market segment of interest selectedat block 402. For example, the precision determiner 206 may provideinstructions to the market segment calculator 208 to use the panelaudience at the selected demographic granularity level for determiningA, B, and/or the ratio A/B, of Table 1 above to calculate D, E, and/or Gof Table 1 above.

If the panel audience size is less than the threshold (block 408), thepanel audience for the demographic granularity level selected at block406 will not be used to attributed collected impressions to the marketsegment s selected at block 402. In such an instance, the exampleprecision determiner 206 determines whether there are additionaldemographic granularity levels (block 412). If there are additionaldemographic granularity levels (block 412), the example returns to block406 to select another demographic granularity level. For example, theprecision determiner 206 may select a next-lowest demographicgranularity level relative to the previously-selected demographicgranularity level, such as Demographic Granularity Level 4 of Table 3above or the Demographic Granularity Level 4 of Table 4 above.

If there are no additional demographic granularity levels (block 412),the example precision determiner 206 determines that the share for themarket segment of interest cannot be estimated with sufficientreliability for the selected demographic group d (block 414). Forexample, because a sufficient sample size cannot be obtained for one ormore demographic groups for the market segment of interest, theprecision of any calculated audience size or impression count may beconsidered to be unacceptably low.

After setting the selected demographic group d to use the panel audienceat the selected demographic granularity level (block 410), or afterdetermining that the share for the market segment s cannot be estimatedwith sufficient reliability (block 414), the precision determiner 206determines whether there are additional demographic groups to be testedfor the selected market segment of interest (block 416). If there areadditional demographic groups to be tested for the selected marketsegment of interest (block 416), control returns to block 404 to selectanother demographic group (e.g., the demographic group female, ages 6-8of Table 3 above, a second one of the BB demographic groups of Table 4above, etc.).

When there are no more demographic groups to be tested (e.g., all of thedemographic groups have been assigned a demographic granularity leveland/or a corresponding panel audience size) (block 416), the examplemarket segment calculator 208 of FIG. 2 determines the share for themarket segment of interest (e.g., the portion of collected impressionsor audience size that is attributable to the market segment of interestfrom a total number of collected impressions or total audience size)using the selected demographic granularity level (block 418). Forexample, the market segment calculator 208 of FIG. 2 may determine themobile audience E (e.g., the share for the selected market segment) ofTable 1 above using the selected panel audiences in the selecteddemographic granularity level. Example instructions to implement block418 to estimate the share for a market segment (e.g., the portion(s) ofthe impression count(s) or audience size(s) attributable to the marketsegment) are described with reference to FIG. 6 below.

The example precision determiner 206 determines whether additionalmarket segment shares are to be estimated (block 420). If there areadditional market segment shares to be estimated (block 420), theexample returns to block 402 to select another market segment ofinterest. When there are no more market segment shares to be estimated(block 420), the example instructions 400 end.

FIG. 5 is a flowchart representative of example computer readableinstructions 500 which may be executed to implement the exampleimpression monitoring server 132 of FIGS. 1 and/or 2 to calculate ashare of a market segment of interest (e.g., the portion of collectedimpressions or audience size that is attributable to the market segmentof interest from a total number of collected impressions or totalaudience size) by selecting a demographic granularity level based oncomparing the panel audience size for the demographic granularity levelto a threshold.

The example precision determiner 206 selects a market segment ofinterest (block 502). For example, the selected market segment ofinterest may be defined by one or more particular demographic attributessuch as household income range, ethnicity, etc. The example precisiondeterminer 206 selects a day-part granularity level (block 504). Forexample, the day-part granularity level may be a particularday/station/¾ hour combination as discussed above with reference toTable 4.

The example precision determiner 206 selects a demographic granularitylevel (block 506). For example, the demographic granularity level may bethe Demographic Granularity Level 1 of Table 3 above or the DemographicGranularity Level 1 of Table 4 above. The example precision determiner206 selects a demographic group in the selected granularity level (block508). For example, the selected demographic group may be the female,ages 2-5 demographic group of Table 3 above or a first demographic groupof the BB demographic groups of Table 4 above.

The example precision determiner 206 determines whether the panelaudience size (e.g., B of Table 1 above) for the selected demographicgroup is less than a threshold (block 510). For example, the thresholdmay be a minimum sample size for the demographic group in the panel. Ifthe panel audience size for the selected demographic group is less thana threshold (block 510), the example precision determiner 206 determineswhether there are additional demographic granularity levels (block 512).If there are additional demographic granularity levels (block 512),control returns to block 506 to select another demographic granularitylevel. For example, a next demographic granularity level, such asDemographic Granularity Level 2 of Table 3 above or the DemographicGranularity Level 2 of Table 4 above, may be selected.

If there are no additional demographic granularity levels (block 512),the example precision determiner 206 determines whether there areadditional day-part granularity level(s) available (block 514). Forexample, a day/station/½ hour granularity level may be used. If thereare additional day-part granularity level(s) available (block 514),control returns to block 504 to select another day-part granularitylevel.

When there are no more day-part granularity level(s) available (block514), the example precision determiner 206 determines that the share ofimpressions for the selected market segment of interest cannot beestimated with sufficient reliability (block 516). For example, becausea sufficient sample size cannot be obtained for one or more demographicgroups for the selected market segment of interest, the precision of anycalculated audience or impressions may be considered to be unacceptablylow.

If, in block 510, the panel audience size for the selected demographicgroup is not less than a threshold, the example precision determiner 206determines whether there are additional demographic groups to be testedat the selected demographic granularity level (block 518). If there areadditional demographic groups to be tested at the selected demographicgranularity level (block 518), control returns to block 508 to selectanother demographic group (e.g., the demographic group female, ages 6-8of Table 3 above, a second one of the BB demographic groups of Table 4above, etc.).

When there are no more demographic groups to be tested at the selecteddemographic granularity level (e.g., all of the demographic groups atthe selected granularity level have at least a threshold panel audiencesize) (block 518), the example market segment calculator 208 estimatesthe share for the market segment of interest using the selecteddemographic granularity level (block 520). For example, the marketsegment calculator 208 may estimate the mobile audience E of Table 1above using the demographic groups in the selected demographicgranularity level. Example instructions that may be executed to estimatethe mobile audience E of Table 1 above are described below withreference to FIG. 6 .

After estimating the share of the market segment of interest (block520), or if the share cannot be estimated with sufficient reliability(block 516), the example market segment calculator 208 determineswhether additional market segment shares are to be estimated (block522). If there are additional market segment shares to be estimated(block 522), control returns to block 502 to select another marketsegment of interest. When there are no more market segment shares to beestimated (block 522), the example instructions 500 end.

FIG. 6 is a flowchart representative of example computer readableinstructions 600 which may be executed to implement the exampleimpression monitoring server 132 of FIGS. 1 and/or 2 to estimate a sharefor a market segment of interest using a selected demographicgranularity level. The example instructions 600 of FIG. 6 may beperformed by the example market segment calculator 208 of FIG. 2 toimplement block 418 of FIG. 4 and/or block 520 of FIG. 5 to estimate ashare for a market segment of interest using a selected demographicgranularity level (e.g., a demographic granularity level selected atblock 406 of FIG. 4 or block 506 of FIG. 5 ).

The example market segment calculator 208 selects a demographic group(e.g., a demographic group d as described above with reference toTable 1) (block 602). The market segment calculator 208 also selects adevice type t (e.g., a device type t as described above with referenceto Table 1) (block 604).

The example market segment calculator 208 accesses a panel audience sizefor the demographic group d at a selected demographic granularity leveland the selected market segment s (e.g., A as described with referenceto Table 1 above) (block 606). The market segment s was previouslyselected by the precision determiner 206 in block 402 of FIG. 4 or inblock 502 of FIG. 5 , and the demographic granularity level waspreviously determined in blocks 404 and 408 of FIG. 4 or in blocks 506and 510 of FIG. 5 .

The market segment calculator 208 of this example also accesses a panelbased audience size for the demographic group d at the selecteddemographic granularity level (e.g., B as described with reference toTable 1 above) (block 608).

The example market segment calculator 208 further accesses a calibratedcensus audience size for the selected demographic group d at thedetermined demographic granularity level and the selected device type t(e.g., C as described with reference to Table 1 above) (block 610). Forexample, the market segment calculator 208 may obtain the calibratedcensus audience size C from the demographics determiner 204 of FIG. 2that includes a number of impressions and/or an audience size that isattributable to the selected demographic group d and the device type t.

The example market segment calculator 208 calculates a device audiencefor the selected demographic group d, the selected market segment s, andthe selected device type t (e.g., D as described with reference to Table1 above) (block 612). For example, the market segment calculator 208 maycalculate the device audience D using the formula D=C×(A/B), whichapplies the ratio or percentage of the market segment to the panelistsin the selected demographic group d to the number of impressions and/oraudience size attributed to the selected demographic group d by thedemographics determiner 204.

The example market segment calculator 208 determines whether there areadditional mobile device types t for which to calculate a deviceaudience D (block 614). If there are additional device types (block614), control returns to block 604 to select a next device type. Whenthere are no more device types (block 614), the example market segmentcalculator 208 calculates a total device audience (e.g., E of Table 1discussed above) for the selected demographic group d, the selectedmarket segment s, and all device types t₁-t_(n) (e.g., devices types forwhich a device audience D was calculated) (block 616). For example, themarket segment calculator 208 may calculate the total device audience Eusing the formula E=Σ_(t)D, or the summation of D over all device typest.

The example market segment calculator 208 accesses the non-mobileaudience size F for the selected demographic group d at the determineddemographic granularity level and the selected market segment s (e.g., Fas described above with reference to Table 1) (block 618). For example,when the total device audience E calculated in block 616 represents onlymobile devices, the market segment calculator 208 may access theaudience for one or more non-mobile device types (e.g., television,radio, desktop computer, etc.).

The example market segment calculator 208 calculates a total audiencesize for the demographic group d at the determined demographicgranularity level and for the market segment s (e.g., G as describedabove with reference to Table 1) (block 620). For example, the marketsegment calculator 208 may calculate the total audience size G using theformula G=F+E. The resulting total audience size and/or number ofimpressions G may be used as a cross-platform ratings measure and/or anaudience measurement.

The example market segment calculator 208 determines whether there areadditional demographic groups for which to calculate total audience sizeG (block 622). For example, the market segment calculator 208 maycalculate the device audience (block 616) and/or the total audience(block 620) for multiple demographic groups. If there are additionaldemographic groups (block 622), control returns to block 602 to selectanother demographic group d. When there are no additional demographicgroups (block 622), the example instructions 600 end and control returnsto a calling function such as block 418 of FIG. 4 and/or block 520 ofFIG. 5 .

FIG. 7 is a block diagram of an example processor platform 700 capableof executing the instructions of FIGS. 4, 5 , and/or 6 to implement theexample impression collector 202, the example demographics determiner204, the example precision determiner 206, the example market segmentcalculator 208 and/or, more generally, the impression monitoring server132 of FIGS. 1 and/or 2 . The processor platform 700 can be, forexample, a server, a personal computer, a mobile device (e.g., a cellphone, a smart phone, a tablet such as an iPad™), or any other type ofcomputing device.

The processor platform 700 of the illustrated example includes aprocessor 712. The processor 712 of the illustrated example is hardware.For example, the processor 712 can be implemented by one or moreintegrated circuits, logic circuits, microprocessors or controllers fromany desired family or manufacturer. The example processor 712 of FIG. 7implements the example impression collector 202, the exampledemographics determiner 204, the example precision determiner 206, theexample market segment calculator 208 and/or, more generally, theimpression monitoring server 132 of FIGS. 1 and/or 2 .

The processor 712 of the illustrated example includes a local memory 713(e.g., a cache). The processor 712 of the illustrated example is incommunication with a main memory including a volatile memory 714 and anon-volatile memory 716 via a bus 718. The volatile memory 714 may beimplemented by Synchronous Dynamic Random Access Memory (SDRAM), DynamicRandom Access Memory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM)and/or any other type of random access memory device. The non-volatilememory 716 may be implemented by flash memory and/or any other desiredtype of memory device. Access to the main memory 714, 716 is controlledby a memory controller.

The processor platform 700 of the illustrated example also includes aninterface circuit 720. The interface circuit 720 may be implemented byany type of interface standard, such as an Ethernet interface, auniversal serial bus (USB), and/or a Peripheral Component Interconnect(PCI) express interface.

In the illustrated example, one or more input devices 722 are connectedto the interface circuit 720. The input device(s) 722 permit(s) a userto enter data and commands into the processor 712. The input device(s)can be implemented by, for example, an audio sensor, a microphone, acamera (still or video), a keyboard, a button, a mouse, a touchscreen, atrack-pad, a trackball, isopoint and/or a voice recognition system.

One or more output devices 724 are also connected to the interfacecircuit 720 of the illustrated example. The output devices 724 can beimplemented, for example, by display devices (e.g., a light emittingdiode (LED), an organic light emitting diode (OLED), a liquid crystaldisplay, a cathode ray tube display (CRT), a touchscreen, a tactileoutput device, a light emitting diode (LED), a printer and/or speakers).The interface circuit 720 of the illustrated example, thus, typicallyincludes a graphics driver card, a graphics driver chip or a graphicsdriver processor.

The interface circuit 720 of the illustrated example also includes acommunication device such as a transmitter, a receiver, a transceiver, amodem and/or network interface card to facilitate exchange of data withexternal machines (e.g., computing devices of any kind) via a network726 (e.g., an Ethernet connection, a digital subscriber line (DSL), atelephone line, coaxial cable, a cellular telephone system, etc.).

The processor platform 700 of the illustrated example also includes oneor more mass storage devices 728 for storing software and/or data.Examples of such mass storage devices 728 include floppy disk drives,hard drive disks, compact disk drives, Blu-ray disk drives, RAIDsystems, and digital versatile disk (DVD) drives.

The coded instructions 732 of FIGS. 4, 5 , and/or 6 may be stored in themass storage device 728, in the volatile memory 714, in the non-volatilememory 716, and/or on a removable tangible computer readable storagemedium such as a CD or DVD.

From the foregoing, it will be appreciated that methods, apparatus andarticles of manufacture have been disclosed which enhance the operationsof a computer to improve the attribution accuracy of distribution ofimpression-based data such as unique audience sizes, impression counts,and duration units to market segments so that computers and processingsystems therein can be relied upon to produce audience analysisinformation with higher accuracies. In some examples, computeroperations can be made more efficient based on the above equations andtechniques for attributing unique audience sizes, impression counts,and/or duration units to market segments. That is, through the use ofthese processes, computers can operate more efficiently by relativelyquickly determining parameters and applying those parameters through theabove disclosed techniques to determine the correct attributions. Forexample, using example processes disclosed herein, a computer can moreefficiently and effectively attribute impressions, audience sizes,and/or durational units in development or test data logged by the AME108 and the database proprietors 104 a-b without using large amounts ofnetwork communication bandwidth (e.g., conserving network communicationbandwidth) and without using large amounts of computer processingresources (e.g., conserving processing resources) to continuouslycommunicate with individual online users (e.g., non-panel online users)to request survey responses about their online media access habits andpersonal details (e.g., personal details relating to which marketsegment(s) they belong) and without needing to rely on such continuoussurvey responses from such online users. Survey responses from onlineusers can be inaccurate due to inabilities or unwillingness of users torecollect online media accesses and/or to divulge personal details foraudience measurement purposes. Survey responses can also be incomplete,which could require additional processor resources to identify andsupplement incomplete survey responses. As such, examples disclosedherein more efficiently and effectively attribute of impressions, uniqueaudience sizes, and/or durational units to market segments. Suchcorrected data is useful in subsequent processing for identifyingexposure performances of different media so that media providers,advertisers, product manufacturers, and/or service providers can makemore informed decisions on how to spend advertising dollars and/or mediaproduction and distribution dollars.

Although certain example methods, apparatus and articles of manufacturehave been disclosed herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe claims of this patent.

What is claimed is:
 1. An apparatus comprising: at least one memory;instructions in the apparatus; and programmable circuitry, theinstructions to cause the programmable circuitry to: access demographicinformation from a database proprietor, the demographic informationcorresponding to impression requests from computing devices indicativeof media impressions; determine a first media impression countcorresponding to a sum of first media impressions that occurred on firstcomputing devices satisfying a device type criterion and that areattributable to a demographic group corresponding to a) the demographicinformation from the database proprietor and b) panel-based demographicinformation corresponding to a market segment of interest; determine asecond media impression count corresponding to second media impressionsthat occurred on second computing devices not satisfying the device typecriterion and that are attributable to the demographic groupcorresponding to a) the demographic information from the databaseproprietor and b) the panel-based demographic information correspondingto the market segment of interest; determine a total media impressioncount by adding the first media impression count to the second mediaimpression count to determine a total number of media impressions thatoccurred on the first and second computing devices that are attributableto the demographic group; and conserve at least one of computingresources or network resources by determining the total media impressioncount without using network communications to request survey responsesrelated to the market segment of interest.
 2. The apparatus of claim 1,wherein the instructions are to cause the programmable circuitry to:obtain, from a panel database, a third media impression countcorresponding to third media impressions attributable to the panel-baseddemographic information corresponding to the market segment of interest;obtain, from the panel database, a fourth media impression countcorresponding to the panel-based demographic information; and determinea ratio of the third media impression count to the fourth mediaimpression count, the ratio corresponding to a portion of thedemographic group that is made up by the market segment of interest; anddetermine the first media impression count based on the ratio.
 3. Theapparatus of claim 1, wherein the instructions are to cause theprogrammable circuitry to: obtain, from a panel database, a third mediaimpression count corresponding to third media impressions attributableto the panel-based demographic information corresponding to the marketsegment of interest; obtain, from the panel database, a fourth mediaimpression count corresponding to the panel-based demographicinformation; and obtain a fifth media impression count corresponding tofourth media impressions that occurred on the first computing devicessatisfying the device type criterion that are attributable to thedemographic information from the database proprietor; determine a ratioof the third media impression count to the fourth media impressioncount, the ratio corresponding to a portion of the demographic groupthat is made up by the market segment of interest; and determine a sixthmedia impression count corresponding to fifth media impressions thatoccurred on the first computing devices that are attributable to thedemographic group, the sixth media impression count to be included inthe sum of the first media impressions that occurred on the firstcomputing devices satisfying the device type criterion.
 4. The apparatusof claim 3, wherein the instructions are to cause the programmablecircuitry to determine the sixth media impression count by multiplyinga) the fifth media impression count and b) the ratio of the third mediaimpression count to the fourth media impression count.
 5. The apparatusof claim 1, wherein the instructions are to cause the programmablecircuitry is to obtain an audience size for a portion of the demographicgroup corresponding to the market segment of interest from the secondcomputing devices not satisfying the device type criterion to determinethe second media impression count.
 6. The apparatus of claim 1, whereinthe first computing devices satisfying the device type criterion aremobile devices and the second computing devices not satisfying thedevice type criterion are non-mobile devices.
 7. The apparatus of claim1, wherein the total media impression count is indicative of a number ofthe first and second media impressions that may be utilized as across-platform ratings measure for the demographic group correspondingto the market segment of interest, the cross-platform ratings measurecorresponding to a total number of computing devices reporting the firstand second media impressions.
 8. A non-transitory computer readablestorage medium comprising instructions to cause programmable circuitryto at least: access demographic information from a database proprietor,the demographic information corresponding to impression requests fromcomputing devices indicative of media impressions; determine a firstmedia impression count corresponding to a sum of first media impressionsthat occurred on first computing devices satisfying a device typecriterion and that are attributable to a demographic group correspondingto a) the demographic information from the database proprietor and b)panel-based demographic information corresponding to a market segment ofinterest; determine a second media impression count corresponding tosecond media impressions that occurred on second computing devices notsatisfying the device type criterion and that are attributable to thedemographic group corresponding to a) the demographic information fromthe database proprietor and b) the panel-based demographic informationcorresponding to the market segment of interest; determine a total mediaimpression count by adding the first media impression count to thesecond media impression count to determine a total number of mediaimpressions that occurred on the first and second computing devices thatare attributable to the demographic group; and conserve at least one ofcomputing resources or network resources by determining the total mediaimpression count without using network communications to request surveyresponses related to the market segment of interest.
 9. Thenon-transitory computer readable storage medium of claim 8, wherein theinstructions are to cause the programmable circuitry to: obtain, from apanel database, a third media impression count corresponding to thirdmedia impressions attributable to the panel-based demographicinformation corresponding to the market segment of interest; obtain,from the panel database, a fourth media impression count correspondingto the panel-based demographic information; and determine a ratio of thethird media impression count to the fourth media impression count, theratio corresponding to a portion of the demographic group that is madeup by the market segment of interest; and determine the first mediaimpression count based on the ratio.
 10. The non-transitory computerreadable storage medium of claim 8, wherein the instructions are tocause the programmable circuitry to: obtain, from a panel database, athird media impression count corresponding to third media impressionsattributable to the panel-based demographic information corresponding tothe market segment of interest; obtain, from the panel database, afourth media impression count corresponding to the panel-baseddemographic information; and obtain a fifth media impression countcorresponding to fourth media impressions that occurred on the firstcomputing devices satisfying the device type criterion that areattributable to the demographic information from the databaseproprietor; determine a ratio of the third media impression count to thefourth media impression count, the ratio corresponding to a portion ofthe demographic group that is made up by the market segment of interest;and determine a sixth media impression count corresponding to fifthmedia impressions that occurred on the first computing devices that areattributable to the demographic group, the sixth media impression countto be included in the sum of the first media impressions that occurredon the first computing devices satisfying the device type criterion. 11.The non-transitory computer readable storage medium of claim 10, whereinthe instructions are to cause the programmable circuitry to determinethe sixth media impression count by multiplying a) the fifth mediaimpression count and b) the ratio of the third media impression count tothe fourth media impression count.
 12. The non-transitory computerreadable storage medium of claim 8, wherein the instructions are tocause the programmable circuitry to obtain an audience size for aportion of the demographic group corresponding to the market segment ofinterest from the second computing devices not satisfying the devicetype criterion to determine the second media impression count.
 13. Thenon-transitory computer readable storage medium of claim 8, wherein thefirst computing devices satisfying the device type criterion are mobiledevices and the second computing devices not satisfying the device typecriterion are non-mobile devices.
 14. The non-transitory computerreadable storage medium of claim 8, wherein the total media impressioncount is indicative of a number of the first and second mediaimpressions that may be utilized as a cross-platform ratings measure forthe demographic group corresponding to the market segment of interest,the cross-platform ratings measure corresponding to a total number ofcomputing devices reporting the first and second media impressions. 15.A method comprising: accessing, by executing an instruction withprogrammable circuitry, demographic information from a databaseproprietor, the demographic information corresponding to impressionrequests from computing devices indicative of media impressions;determining, by executing an instruction with the programmablecircuitry, a first media impression count corresponding to a sum offirst media impressions that occurred on first computing devicessatisfying a device type criterion and that are attributable to ademographic group corresponding to a) the demographic information fromthe database proprietor and b) panel-based demographic informationcorresponding to a market segment of interest; determining, by executingan instruction with the programmable circuitry, a second mediaimpression count corresponding to second media impressions that occurredon second computing devices not satisfying the device type criterion andthat are attributable to the demographic group corresponding to a) thedemographic information from the database proprietor and b) thepanel-based demographic information corresponding to the market segmentof interest; and determining, by executing an instruction with theprogrammable circuitry, a total media impression count without usingnetwork communications to request survey responses related to the marketsegment of interest to conserve at least one of computing resources ornetwork resources by adding the first media impression count to thesecond media impression count to determine a total number of mediaimpressions that occurred on the first and second computing devices thatare attributable to the demographic group.
 16. The method of claim 15,further including: obtaining, from a panel database, a third mediaimpression count corresponding to third media impressions attributableto the panel-based demographic information corresponding to the marketsegment of interest; obtaining, from the panel database, a fourth mediaimpression count corresponding to the panel-based demographicinformation; and obtaining a fifth media impression count correspondingto fourth media impressions that occurred on the first computing devicessatisfying the device type criterion that are attributable to thedemographic information from the database proprietor; determining aratio of the third media impression count to the fourth media impressioncount, the ratio corresponding to a portion of the demographic groupthat is made up by the market segment of interest; and determining asixth media impression count corresponding to fifth media impressionsthat occurred on the first computing devices that are attributable tothe demographic group, the sixth media impression count to be includedin the sum of the first media impressions that occurred on the firstcomputing devices satisfying the device type criterion.
 17. The methodof claim 16, further including determining the sixth media impressioncount by multiplying a) the fifth media impression count and b) theratio of the third media impression count to the fourth media impressioncount.
 18. The method of claim 15, further including obtaining anaudience size for a portion of the demographic group corresponding tothe market segment of interest from the second computing devices notsatisfying the device type criterion to determine the second mediaimpression count.
 19. The method of claim 15, wherein the firstcomputing devices satisfying the device type criterion are mobiledevices and the second computing devices not satisfying the device typecriterion are non-mobile devices.
 20. The method of claim 15, whereinthe total media impression count is indicative of a number of the firstand second media impressions that may be utilized as a cross-platformratings measure for the demographic group corresponding to the marketsegment of interest, the cross-platform ratings measure corresponding toa total number of computing devices reporting the first and second mediaimpressions.